IVGCVSW-6453 'Move the ArmNN Test Utils code to a physically separate directory'
* Created include/armnnTestUtils directory
* Moved Arm NN test utils files into armnnTestUtils directory
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: I03ac54c645c41c52650c4c03b6a58fb1481fef5d
diff --git a/src/armnn/test/CreateWorkload.hpp b/src/armnn/test/CreateWorkload.hpp
index ea8a436..ae07253 100644
--- a/src/armnn/test/CreateWorkload.hpp
+++ b/src/armnn/test/CreateWorkload.hpp
@@ -2,2315 +2,8 @@
// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
-#include "TestUtils.hpp"
-
-#include <Graph.hpp>
-#include <Network.hpp>
-#include <ResolveType.hpp>
-
-#include <armnnUtils/DataLayoutIndexed.hpp>
-#include <armnn/utility/Assert.hpp>
-#include <armnn/utility/IgnoreUnused.hpp>
-#include <armnn/utility/PolymorphicDowncast.hpp>
-
-#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/WorkloadData.hpp>
-#include <backendsCommon/WorkloadFactory.hpp>
-
-#include <doctest/doctest.h>
-
-#include <utility>
-
-using namespace armnn;
-
-namespace
-{
-
-using namespace std;
-
-// Calls CreateWorkload for a layer, and checks the returned pointer is of the correct type.
-template<typename Workload>
-std::unique_ptr<Workload> MakeAndCheckWorkload(Layer& layer,
- const IWorkloadFactory& factory,
- const ModelOptions& modelOptions = {})
-{
- std::unique_ptr<IWorkload> workload = layer.CreateWorkload(factory);
- CHECK_MESSAGE(workload.get() == PolymorphicDowncast<Workload*>(workload.get()),
- "Cannot convert to derived class");
- std::string reasonIfUnsupported;
- layer.SetBackendId(factory.GetBackendId());
- CHECK(factory.IsLayerSupported(layer, layer.GetDataType(), reasonIfUnsupported, modelOptions));
- return std::unique_ptr<Workload>(static_cast<Workload*>(workload.release()));
-}
-
-// Helper function to create tensor handlers for workloads, assuming they all use the same factory.
-void CreateTensorHandles(armnn::Graph& graph,
- armnn::IWorkloadFactory& factory)
-{
- TensorHandleFactoryRegistry tmpRegistry;
- for (auto&& layer : graph.TopologicalSort())
- {
- layer->CreateTensorHandles(tmpRegistry, factory);
- }
-}
-
-/////////////////////////////////////////////////////////////////////////////////////////////
-// The following functions are called by backendsCommon/test/CreateWorkload*.cpp
-// They build very simple graphs, and then create a workload.
-// Some checks are performed on the workload to ensure parameters have been passed correctly.
-// They return the created workloads so that backend-specific checks can be performed.
-/////////////////////////////////////////////////////////////////////////////////////////////
-
-template <typename ActivationWorkload, armnn::DataType DataType>
-std::unique_ptr<ActivationWorkload> CreateActivationWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- // Creates the layer we're testing.
- ActivationDescriptor layerDesc;
- layerDesc.m_Function = ActivationFunction::Abs;
- layerDesc.m_A = 3.5f;
- layerDesc.m_B = -10.0f;
-
- ActivationLayer* const layer = graph.AddLayer<ActivationLayer>(layerDesc, "layer");
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo tensorInfo({1, 1}, DataType);
-
- Connect(input, layer, tensorInfo);
- Connect(layer, output, tensorInfo);
-
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<ActivationWorkload>(*layer, factory);
-
- ActivationQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
- CHECK(queueDescriptor.m_Parameters.m_A == 3.5f);
- CHECK(queueDescriptor.m_Parameters.m_B == -10.0f);
- CHECK((queueDescriptor.m_Parameters.m_Function == ActivationFunction::Abs));
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename WorkloadType,
- typename DescriptorType,
- typename LayerType,
- armnn::DataType DataType>
-std::unique_ptr<WorkloadType> CreateElementwiseWorkloadTest(armnn::IWorkloadFactory & factory,
- armnn::Graph & graph)
-{
- // Creates the layer we're testing.
- Layer* const layer = graph.AddLayer<LayerType>("layer");
-
- // Creates extra layers.
- Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");
- Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo tensorInfo({2, 3}, DataType);
- Connect(input1, layer, tensorInfo, 0, 0);
- Connect(input2, layer, tensorInfo, 0, 1);
- Connect(layer, output, tensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);
-
- DescriptorType queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 2);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template<typename WorkloadType,
- typename DescriptorType,
- armnn::DataType DataType>
-std::unique_ptr<WorkloadType> CreateSubtractionWithBlobWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- // Creates the layer we're testing.
- SubtractionLayer* const layer = graph.AddLayer<SubtractionLayer>("layer");
-
- auto activationDesc = std::make_shared<ActivationDescriptor>();
- activationDesc->m_A = 10.0f;
- activationDesc->m_B = 5.0f;
- activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
-
- layer->SetAdditionalInfoForObject(activationDesc);
-
- // Creates extra layers.
- Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");
- Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo tensorInfo({2, 3}, DataType);
- Connect(input1, layer, tensorInfo, 0, 0);
- Connect(input2, layer, tensorInfo, 0, 1);
- Connect(layer, output, tensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Check that the additional information can be queried from the layer
- std::shared_ptr<ActivationDescriptor>
- activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();
-
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
- ARMNN_ASSERT(
- static_cast<ActivationFunction>(activationDescPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
- );
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);
-
- DescriptorType queueDescriptor = workload->GetData();
-
- const ActivationDescriptor* queueDescBlobPtr =
- queueDescriptor.template GetAdditionalInformation<ActivationDescriptor>();
- IgnoreUnused(queueDescBlobPtr);
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
- ARMNN_ASSERT(
- static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
- );
-
- CHECK(queueDescriptor.m_Inputs.size() == 2);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- return workload;
-}
-
-template<typename WorkloadType,
- typename DescriptorType,
- armnn::DataType DataType>
-std::unique_ptr<WorkloadType> CreateMultiplicationWithBlobWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- // Creates the layer we're testing.
- MultiplicationLayer* const layer = graph.AddLayer<MultiplicationLayer>("layer");
-
- auto activationDesc = std::make_shared<ActivationDescriptor>();
- activationDesc->m_A = 10.0f;
- activationDesc->m_B = 5.0f;
- activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
-
- layer->SetAdditionalInfoForObject(activationDesc);
-
- // Creates extra layers.
- Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");
- Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo tensorInfo({2, 3}, DataType);
- Connect(input1, layer, tensorInfo, 0, 0);
- Connect(input2, layer, tensorInfo, 0, 1);
- Connect(layer, output, tensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Check that the additional information can be queried from the layer
- std::shared_ptr<ActivationDescriptor>
- activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();
-
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
- ARMNN_ASSERT(
- static_cast<ActivationFunction>(activationDescPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
- );
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);
-
- DescriptorType queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 2);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
- const ActivationDescriptor* queueDescBlobPtr =
- queueDescriptor.template GetAdditionalInformation<ActivationDescriptor>();
- IgnoreUnused(queueDescBlobPtr);
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
- ARMNN_ASSERT(
- static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
- );
-
- return workload;// Returns so we can do extra, backend-specific tests.
-}
-
-template<typename WorkloadType,
- typename DescriptorType,
- armnn::DataType DataType>
-std::unique_ptr<WorkloadType> CreateAdditionWithBlobWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- // Creates the layer we're testing.
- AdditionLayer* const layer = graph.AddLayer<AdditionLayer>("layer");
-
- auto activationDesc = std::make_shared<ActivationDescriptor>();
- activationDesc->m_A = 10.0f;
- activationDesc->m_B = 5.0f;
- activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
-
- layer->SetAdditionalInfoForObject(activationDesc);
-
- // Creates extra layers.
- Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");
- Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo tensorInfo({2, 3}, DataType);
- Connect(input1, layer, tensorInfo, 0, 0);
- Connect(input2, layer, tensorInfo, 0, 1);
- Connect(layer, output, tensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Check that the additional information can be queried from the layer
- std::shared_ptr<ActivationDescriptor>
- activationDescPtr = layer->template GetAdditionalInformation<ActivationDescriptor>();
-
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
- ARMNN_ASSERT(
- static_cast<ActivationFunction>(activationDescPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
- );
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);
-
- DescriptorType queueDescriptor = workload->GetData();
- const ActivationDescriptor* queueDescBlobPtr =
- queueDescriptor.template GetAdditionalInformation<ActivationDescriptor>();
- IgnoreUnused(queueDescBlobPtr);
- CHECK(queueDescriptor.m_Inputs.size() == 2);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
- ARMNN_ASSERT(
- static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
- );
-
- return workload;
-}
-
-template <typename WorkloadType,
- typename DescriptorType,
- armnn::DataType DataType>
-std::unique_ptr<WorkloadType> CreateElementwiseUnaryWorkloadTest(armnn::IWorkloadFactory & factory,
- armnn::Graph & graph,
- armnn::UnaryOperation op)
-{
- ElementwiseUnaryDescriptor desc = ElementwiseUnaryDescriptor(op);
- Layer* const layer = graph.AddLayer<armnn::ElementwiseUnaryLayer>(desc, "layer");
-
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- armnn::TensorInfo tensorInfo({ 2, 3 }, DataType);
- Connect(input, layer, tensorInfo, 0, 0);
- Connect(layer, output, tensorInfo, 0, 0);
- CreateTensorHandles(graph, factory);
-
- auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);
- DescriptorType queueDescriptor = workload->GetData();
-
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- return workload;
-}
-
-template <typename BatchNormalizationWorkloadType, armnn::DataType DataType>
-std::unique_ptr<BatchNormalizationWorkloadType> CreateBatchNormalizationWorkloadTest(
- armnn::IWorkloadFactory& factory, armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW)
-{
- TensorShape tensorShape;
- switch (dataLayout)
- {
- case DataLayout::NHWC:
- tensorShape = { 2, 4, 4, 3 };
- break;
- case DataLayout::NCHW:
- default:
- tensorShape = { 2, 3, 4, 4 };
- }
-
- // Creates the layer we're testing.
- BatchNormalizationDescriptor layerDesc;
- layerDesc.m_Eps = 0.05f;
- layerDesc.m_DataLayout = dataLayout;
-
- BatchNormalizationLayer* const layer = graph.AddLayer<BatchNormalizationLayer>(layerDesc, "layer");
-
- armnn::TensorInfo weightInfo({3}, DataType);
- layer->m_Mean = std::make_unique<ScopedTensorHandle>(weightInfo);
- layer->m_Variance = std::make_unique<ScopedTensorHandle>(weightInfo);
- layer->m_Beta = std::make_unique<ScopedTensorHandle>(weightInfo);
- layer->m_Gamma = std::make_unique<ScopedTensorHandle>(weightInfo);
- layer->m_Mean->Allocate();
- layer->m_Variance->Allocate();
- layer->m_Beta->Allocate();
- layer->m_Gamma->Allocate();
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo tensorInfo(tensorShape, DataType);
- Connect(input, layer, tensorInfo);
- Connect(layer, output, tensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<BatchNormalizationWorkloadType>(*layer, factory);
- BatchNormalizationQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Parameters.m_Eps == 0.05f);
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
- CHECK((queueDescriptor.m_Mean->GetTensorInfo() == TensorInfo({3}, DataType)));
- CHECK((queueDescriptor.m_Variance->GetTensorInfo() == TensorInfo({3}, DataType)));
- CHECK((queueDescriptor.m_Gamma->GetTensorInfo() == TensorInfo({3}, DataType)));
- CHECK((queueDescriptor.m_Beta->GetTensorInfo() == TensorInfo({3}, DataType)));
- CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename BatchNormalizationWorkloadType, armnn::DataType DataType>
-std::unique_ptr<BatchNormalizationWorkloadType> CreateBatchNormalizationWithBlobWorkloadTest(
- armnn::IWorkloadFactory& factory, armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW)
-{
- TensorShape tensorShape;
- switch (dataLayout)
- {
- case DataLayout::NHWC:
- tensorShape = { 2, 4, 4, 3 };
- break;
- case DataLayout::NCHW:
- default:
- tensorShape = { 2, 3, 4, 4 };
- }
-
- // Creates the layer we're testing.
- BatchNormalizationDescriptor layerDesc;
- layerDesc.m_Eps = 0.05f;
- layerDesc.m_DataLayout = dataLayout;
-
- BatchNormalizationLayer* const layer = graph.AddLayer<BatchNormalizationLayer>(layerDesc, "layer");
-
- armnn::TensorInfo weightInfo({3}, DataType);
- layer->m_Mean = std::make_unique<ScopedTensorHandle>(weightInfo);
- layer->m_Variance = std::make_unique<ScopedTensorHandle>(weightInfo);
- layer->m_Beta = std::make_unique<ScopedTensorHandle>(weightInfo);
- layer->m_Gamma = std::make_unique<ScopedTensorHandle>(weightInfo);
- layer->m_Mean->Allocate();
- layer->m_Variance->Allocate();
- layer->m_Beta->Allocate();
- layer->m_Gamma->Allocate();
-
- auto activationDesc = std::make_shared<ActivationDescriptor>();
- activationDesc->m_A = 10.0f;
- activationDesc->m_B = 5.0f;
- activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
-
- layer->SetAdditionalInfoForObject(activationDesc);
-
- // Check that the additional information can be queried from the layer
- std::shared_ptr<ActivationDescriptor> activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
- ARMNN_ASSERT(
- static_cast<ActivationFunction>(activationDescPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
- );
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo tensorInfo(tensorShape, DataType);
- Connect(input, layer, tensorInfo);
- Connect(layer, output, tensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<BatchNormalizationWorkloadType>(*layer, factory);
- BatchNormalizationQueueDescriptor queueDescriptor = workload->GetData();
- const ActivationDescriptor* queueDescBlobPtr = queueDescriptor.GetAdditionalInformation<ActivationDescriptor>();
- IgnoreUnused(queueDescBlobPtr);
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
- ARMNN_ASSERT(
- static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
- );
-
- CHECK(queueDescriptor.m_Parameters.m_Eps == 0.05f);
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
- CHECK((queueDescriptor.m_Mean->GetTensorInfo() == TensorInfo({3}, DataType)));
- CHECK((queueDescriptor.m_Variance->GetTensorInfo() == TensorInfo({3}, DataType)));
- CHECK((queueDescriptor.m_Gamma->GetTensorInfo() == TensorInfo({3}, DataType)));
- CHECK((queueDescriptor.m_Beta->GetTensorInfo() == TensorInfo({3}, DataType)));
- CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename Convolution2dWorkload, armnn::DataType DataType>
-std::unique_ptr<Convolution2dWorkload> CreateConvolution2dWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph,
- DataLayout dataLayout = DataLayout::NCHW,
- const ModelOptions& modelOptions = {})
-{
- // Creates 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;
- layerDesc.m_DataLayout = dataLayout;
-
- Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");
-
- TensorShape weightShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 5, 3} : TensorShape{2, 5, 3, 3};
- TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 8, 16} : TensorShape{2, 8, 16, 3};
- TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 2, 2, 10} : TensorShape{2, 2, 10, 2};
-
- layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo(weightShape, DataType));
- layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({2}, GetBiasDataType(DataType)));
-
- layer->m_Weight->Allocate();
- layer->m_Bias->Allocate();
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- Connect(input, layer, TensorInfo(inputShape, DataType));
- Connect(layer, output, TensorInfo(outputShape, DataType));
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory, modelOptions);
-
- Convolution2dQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Parameters.m_StrideX == 2);
- CHECK(queueDescriptor.m_Parameters.m_StrideY == 4);
- CHECK(queueDescriptor.m_Parameters.m_PadLeft == 3);
- CHECK(queueDescriptor.m_Parameters.m_PadRight == 3);
- CHECK(queueDescriptor.m_Parameters.m_PadTop == 1);
- CHECK(queueDescriptor.m_Parameters.m_PadBottom == 1);
- CHECK(queueDescriptor.m_Parameters.m_BiasEnabled);
- CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
-
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
- CHECK((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo(weightShape, DataType)));
- CHECK((queueDescriptor.m_Bias->GetTensorInfo() ==
- TensorInfo({2}, GetBiasDataType(DataType))));
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template<typename Convolution2dWorkload, armnn::DataType DataType>
-std::unique_ptr<Convolution2dWorkload> CreateConvolution2dFusedActivationWithBlobWorkloadTest(
- armnn::IWorkloadFactory& factory,
- armnn::Graph& graph,
- DataLayout dataLayout = DataLayout::NCHW,
- const ModelOptions& modelOptions = {})
-{
- // Creates 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;
- layerDesc.m_DataLayout = dataLayout;
-
-
- Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");
-
- TensorShape weightShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 5, 3} : TensorShape{2, 5, 3, 3};
- TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 8, 16} : TensorShape{2, 8, 16, 3};
- TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 2, 2, 10} : TensorShape{2, 2, 10, 2};
-
- layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo(weightShape, DataType));
- layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({2}, GetBiasDataType(DataType)));
-
- layer->m_Weight->Allocate();
- layer->m_Bias->Allocate();
-
- auto activationDesc = std::make_shared<ActivationDescriptor>();
- activationDesc->m_A = 10.0f;
- activationDesc->m_B = 5.0f;
- activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
-
- layer->SetAdditionalInfoForObject(activationDesc);
-
- // Check that the additional information can be queried from the layer
- std::shared_ptr<ActivationDescriptor> activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();
-
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
- ARMNN_ASSERT(
- static_cast<ActivationFunction>(activationDescPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
- );
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- Connect(input, layer, TensorInfo(inputShape, DataType));
- Connect(layer, output, TensorInfo(outputShape, DataType));
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory, modelOptions);
-
- Convolution2dQueueDescriptor queueDescriptor = workload->GetData();
- const ActivationDescriptor* queueDescBlobPtr = queueDescriptor.GetAdditionalInformation<ActivationDescriptor>();
- IgnoreUnused(queueDescBlobPtr);
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
- ARMNN_ASSERT(
- static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
- );
-
- CHECK(queueDescriptor.m_Parameters.m_StrideX == 2);
- CHECK(queueDescriptor.m_Parameters.m_StrideY == 4);
- CHECK(queueDescriptor.m_Parameters.m_PadLeft == 3);
- CHECK(queueDescriptor.m_Parameters.m_PadRight == 3);
- CHECK(queueDescriptor.m_Parameters.m_PadTop == 1);
- CHECK(queueDescriptor.m_Parameters.m_PadBottom == 1);
- CHECK(queueDescriptor.m_Parameters.m_BiasEnabled);
- CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
- CHECK(queueDescriptor.m_Outputs.size() == 1);
- CHECK((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo(weightShape, DataType)));
- CHECK((queueDescriptor.m_Bias->GetTensorInfo() ==
- TensorInfo({2}, GetBiasDataType(DataType))));
- CHECK(queueDescriptor.m_Inputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename Convolution2dWorkload, armnn::DataType DataType>
-std::unique_ptr<Convolution2dWorkload> CreateConvolution2dWorkloadFastMathTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph,
- DataLayout dataLayout = DataLayout::NCHW,
- const ModelOptions& modelOptions = {})
-{
- // Creates the layer we're testing.
- Convolution2dDescriptor layerDesc;
- layerDesc.m_PadLeft = 0;
- layerDesc.m_PadRight = 0;
- layerDesc.m_PadTop = 0;
- layerDesc.m_PadBottom = 0;
- layerDesc.m_StrideX = 1;
- layerDesc.m_StrideY = 1;
- layerDesc.m_BiasEnabled = false;
- layerDesc.m_DataLayout = dataLayout;
-
- Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");
-
- TensorShape weightShape = TensorShape{32, 32, 3, 3};
- TensorShape inputShape = TensorShape{1, 32, 149, 149};
- TensorShape outputShape = TensorShape{1, 32, 147, 147};
-
- layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo(weightShape, DataType));
- layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({2}, GetBiasDataType(DataType)));
-
- layer->m_Weight->Allocate();
- layer->m_Bias->Allocate();
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- Connect(input, layer, TensorInfo(inputShape, DataType));
- Connect(layer, output, TensorInfo(outputShape, DataType));
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory, modelOptions);
-
- Convolution2dQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Parameters.m_StrideX == 1);
- CHECK(queueDescriptor.m_Parameters.m_StrideY == 1);
- CHECK(queueDescriptor.m_Parameters.m_PadLeft == 0);
- CHECK(queueDescriptor.m_Parameters.m_PadRight == 0);
- CHECK(queueDescriptor.m_Parameters.m_PadTop == 0);
- CHECK(queueDescriptor.m_Parameters.m_PadBottom == 0);
- CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
-
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
- CHECK((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo(weightShape, DataType)));
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename LstmWorkload>
-std::unique_ptr<LstmWorkload> CreateLstmWorkloadTest(armnn::IWorkloadFactory& factory, armnn::Graph& graph)
-{
- // This parameter setting is for withCifgWithPeepholeNoProjection
- LstmDescriptor layerDesc;
- layerDesc.m_ActivationFunc = 4;
- layerDesc.m_ClippingThresCell = 0.0f;
- layerDesc.m_ClippingThresProj = 0.0f;
- layerDesc.m_CifgEnabled = true;
- layerDesc.m_PeepholeEnabled = true;
- layerDesc.m_ProjectionEnabled = false;
-
- LstmLayer* const layer = graph.AddLayer<LstmLayer>(layerDesc, "layer");
- unsigned int batchSize = 2;
- unsigned int inputSize = 2;
- unsigned int numUnits = 4;
- unsigned int outputSize = 4;
-
- layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>
- (TensorInfo({ numUnits, inputSize }, DataType::Float32));
- layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>
- (TensorInfo({ numUnits, inputSize }, DataType::Float32));
- layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<ScopedTensorHandle>
- (TensorInfo({ numUnits, inputSize }, DataType::Float32));
- layer->m_BasicParameters.m_RecurrentToForgetWeights = std::make_unique<ScopedTensorHandle>
- (TensorInfo({ numUnits, outputSize }, DataType::Float32));
- layer->m_BasicParameters.m_RecurrentToCellWeights = std::make_unique<ScopedTensorHandle>
- (TensorInfo({ numUnits, outputSize }, DataType::Float32));
- layer->m_BasicParameters.m_RecurrentToOutputWeights = std::make_unique<ScopedTensorHandle>
- (TensorInfo({ numUnits, outputSize }, DataType::Float32));
- layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<ScopedTensorHandle>
- (TensorInfo({ numUnits }, DataType::Float32));
- layer->m_BasicParameters.m_CellBias = std::make_unique<ScopedTensorHandle>
- (TensorInfo({ numUnits }, DataType::Float32));
- layer->m_BasicParameters.m_OutputGateBias = std::make_unique<ScopedTensorHandle>
- (TensorInfo({ numUnits }, DataType::Float32));
-
- layer->m_BasicParameters.m_InputToForgetWeights->Allocate();
- layer->m_BasicParameters.m_InputToCellWeights->Allocate();
- layer->m_BasicParameters.m_InputToOutputWeights->Allocate();
- layer->m_BasicParameters.m_RecurrentToForgetWeights->Allocate();
- layer->m_BasicParameters.m_RecurrentToCellWeights->Allocate();
- layer->m_BasicParameters.m_RecurrentToOutputWeights->Allocate();
- layer->m_BasicParameters.m_ForgetGateBias->Allocate();
- layer->m_BasicParameters.m_CellBias->Allocate();
- layer->m_BasicParameters.m_OutputGateBias->Allocate();
-
-
- if (layerDesc.m_PeepholeEnabled)
- {
- layer->m_PeepholeParameters.m_CellToForgetWeights = std::make_unique<ScopedTensorHandle>
- (TensorInfo({ numUnits }, DataType::Float32));
- layer->m_PeepholeParameters.m_CellToOutputWeights = std::make_unique<ScopedTensorHandle>
- (TensorInfo({ numUnits }, DataType::Float32));
- layer->m_PeepholeParameters.m_CellToForgetWeights->Allocate();
- layer->m_PeepholeParameters.m_CellToOutputWeights->Allocate();
- }
-
- // create input and output layers
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const outputStateIn = graph.AddLayer<InputLayer>(1, "outputStateIn");
- Layer* const cellStateIn = graph.AddLayer<InputLayer>(2, "cellStateIn");
- Layer* const scratchBuffer = graph.AddLayer<OutputLayer>(0, "scratchBuffer");
- Layer* const outputStateOut = graph.AddLayer<OutputLayer>(1, "outputStateOut");
- Layer* const cellStateOut = graph.AddLayer<OutputLayer>(2, "cellStateOut");
- Layer* const output = graph.AddLayer<OutputLayer>(3, "output");
-
- // connect up
- armnn::TensorInfo lstmTensorInfo1({ batchSize, inputSize }, DataType::Float32);
- armnn::TensorInfo lstmTensorInfo2({ batchSize, numUnits}, DataType::Float32);
- armnn::TensorInfo lstmTensorInfo3({ batchSize, outputSize }, DataType::Float32);
- armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * (layerDesc.m_CifgEnabled ? 3 : 4) },
- DataType::Float32);
- Connect(input, layer, lstmTensorInfo1, 0, 0);
- Connect(cellStateIn, layer, lstmTensorInfo2, 0, 1);
- Connect(outputStateIn, layer, lstmTensorInfo3, 0, 2);
- Connect(layer, scratchBuffer, lstmTensorInfoScratchBuff, 0, 0);
- Connect(layer, outputStateOut, lstmTensorInfo3, 1, 0);
- Connect(layer, cellStateOut, lstmTensorInfo2, 2, 0);
- Connect(layer, output, lstmTensorInfo3, 3, 0);
-
- CreateTensorHandles(graph, factory);
-
- // make the workload and check it
- auto workload = MakeAndCheckWorkload<LstmWorkload>(*layer, factory);
- LstmQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Parameters.m_ActivationFunc == 4);
- CHECK(queueDescriptor.m_Parameters.m_ClippingThresCell == 0.0f);
- CHECK(queueDescriptor.m_Parameters.m_ClippingThresProj == 0.0f);
- CHECK(queueDescriptor.m_Inputs.size() == 3);
- CHECK(queueDescriptor.m_Outputs.size() == 4);
-
- CHECK((queueDescriptor.m_InputToForgetWeights->GetTensorInfo() == TensorInfo({ numUnits, inputSize },
- DataType::Float32)));
- CHECK((queueDescriptor.m_OutputGateBias->GetTensorInfo() == TensorInfo({ numUnits },
- DataType::Float32)));
- CHECK((queueDescriptor.m_CellBias->GetTensorInfo() == TensorInfo({ numUnits }, DataType::Float32)));
- return workload;
-}
-
-template <typename QuantizedLstmWorkload>
-std::unique_ptr<QuantizedLstmWorkload> CreateQuantizedLstmWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- auto layer = graph.AddLayer<QuantizedLstmLayer>("quantizedLstmlayer");
- unsigned int numBatches = 2;
- unsigned int inputSize = 2;
- unsigned int outputSize = 4;
-
- // Scale/Offset for input/output, cellState In/Out, weights, bias
- float inputOutputScale = 0.0078125f;
- int32_t inputOutputOffset = 128;
-
- float cellStateScale = 0.00048828125f;
- int32_t cellStateOffset = 0;
-
- float weightsScale = 0.00408021f;
- int32_t weightsOffset = 100;
-
- float biasScale = 3.1876640625e-05f;
- int32_t biasOffset = 0;
-
- // Weights and bias tensor and quantization info
- armnn::TensorInfo inputWeightsInfo({outputSize, inputSize},
- armnn::DataType::QAsymmU8,
- weightsScale,
- weightsOffset);
-
- armnn::TensorInfo recurrentWeightsInfo({outputSize, outputSize},
- armnn::DataType::QAsymmU8,
- weightsScale,
- weightsOffset);
-
- armnn::TensorInfo biasInfo({outputSize},
- armnn::DataType::Signed32,
- biasScale,
- biasOffset);
-
- // Weights and bias
- layer->m_QuantizedLstmParameters.m_InputToInputWeights =
- std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
- layer->m_QuantizedLstmParameters.m_InputToForgetWeights =
- std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
- layer->m_QuantizedLstmParameters.m_InputToCellWeights =
- std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
- layer->m_QuantizedLstmParameters.m_InputToOutputWeights =
- std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
-
- layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights =
- std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
- layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights =
- std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
- layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights =
- std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
- layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights =
- std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
-
- layer->m_QuantizedLstmParameters.m_InputGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);
- layer->m_QuantizedLstmParameters.m_ForgetGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);
- layer->m_QuantizedLstmParameters.m_CellBias = std::make_unique<ScopedTensorHandle>(biasInfo);
- layer->m_QuantizedLstmParameters.m_OutputGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);
-
- // Allocate weights and bias
- layer->m_QuantizedLstmParameters.m_InputToInputWeights->Allocate();
- layer->m_QuantizedLstmParameters.m_InputToForgetWeights->Allocate();
- layer->m_QuantizedLstmParameters.m_InputToCellWeights->Allocate();
- layer->m_QuantizedLstmParameters.m_InputToOutputWeights->Allocate();
-
- layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights->Allocate();
- layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights->Allocate();
- layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights->Allocate();
- layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights->Allocate();
-
- layer->m_QuantizedLstmParameters.m_InputGateBias->Allocate();
- layer->m_QuantizedLstmParameters.m_ForgetGateBias->Allocate();
- layer->m_QuantizedLstmParameters.m_CellBias->Allocate();
- layer->m_QuantizedLstmParameters.m_OutputGateBias->Allocate();
-
- // Create input and output layers
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const cellStateIn = graph.AddLayer<InputLayer>(1, "cellStateIn");
- Layer* const outputStateIn = graph.AddLayer<InputLayer>(2, "outputStateIn");
-
- Layer* const cellStateOut = graph.AddLayer<OutputLayer>(0, "cellStateOut");
- Layer* const outputStateOut = graph.AddLayer<OutputLayer>(1, "outputStateOut");
-
- // Input/output tensor info and quantization info
- armnn::TensorInfo inputInfo({numBatches , inputSize},
- armnn::DataType::QAsymmU8,
- inputOutputScale,
- inputOutputOffset);
-
- armnn::TensorInfo cellStateInfo({numBatches , outputSize},
- armnn::DataType::QSymmS16,
- cellStateScale,
- cellStateOffset);
-
- armnn::TensorInfo outputStateInfo({numBatches , outputSize},
- armnn::DataType::QAsymmU8,
- inputOutputScale,
- inputOutputOffset);
-
- // Connect input/output slots
- Connect(input, layer, inputInfo, 0, 0);
- Connect(cellStateIn, layer, cellStateInfo, 0, 1);
- Connect(outputStateIn, layer, outputStateInfo, 0, 2);
-
- Connect(layer, cellStateOut, cellStateInfo, 0, 0);
- Connect(layer, outputStateOut, outputStateInfo, 1, 0);
-
- CreateTensorHandles(graph, factory);
-
- // Create workload and check layer support
- auto workload = MakeAndCheckWorkload<QuantizedLstmWorkload>(*layer, factory);
- QuantizedLstmQueueDescriptor queueDescriptor = workload->GetData();
-
- // Validate input/output sizes
- CHECK(queueDescriptor.m_Inputs.size() == 3);
- CHECK(queueDescriptor.m_Outputs.size() == 2);
-
- // Validate weight tensor info
- CHECK((queueDescriptor.m_InputToInputWeights->GetTensorInfo() == inputWeightsInfo));
- CHECK((queueDescriptor.m_InputToForgetWeights->GetTensorInfo() == inputWeightsInfo));
- CHECK((queueDescriptor.m_InputToCellWeights->GetTensorInfo() == inputWeightsInfo));
- CHECK((queueDescriptor.m_InputToOutputWeights->GetTensorInfo() == inputWeightsInfo));
-
- CHECK((queueDescriptor.m_RecurrentToInputWeights->GetTensorInfo() == recurrentWeightsInfo));
- CHECK((queueDescriptor.m_RecurrentToForgetWeights->GetTensorInfo() == recurrentWeightsInfo));
- CHECK((queueDescriptor.m_RecurrentToCellWeights->GetTensorInfo() == recurrentWeightsInfo));
- CHECK((queueDescriptor.m_RecurrentToOutputWeights->GetTensorInfo() == recurrentWeightsInfo));
-
- CHECK((queueDescriptor.m_InputGateBias->GetTensorInfo() == biasInfo));
- CHECK((queueDescriptor.m_ForgetGateBias->GetTensorInfo() == biasInfo));
- CHECK((queueDescriptor.m_CellBias->GetTensorInfo() == biasInfo));
- CHECK((queueDescriptor.m_OutputGateBias->GetTensorInfo() == biasInfo));
-
- return workload;
-}
-
-template <typename QLstmWorkload>
-std::unique_ptr<QLstmWorkload> CreateQLstmWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- QLstmDescriptor layerDesc;
- layerDesc.m_CifgEnabled = true;
- layerDesc.m_PeepholeEnabled = false;
- layerDesc.m_ProjectionEnabled = false;
- layerDesc.m_LayerNormEnabled = true;
-
- layerDesc.m_CellClip = 0.0f;
- layerDesc.m_ProjectionClip = 0.0f;
-
- layerDesc.m_HiddenStateZeroPoint = 0;
- layerDesc.m_HiddenStateScale = 0.007f;
-
- layerDesc.m_InputIntermediateScale = 0.007059f;
- layerDesc.m_ForgetIntermediateScale = 0.007812f;
- layerDesc.m_CellIntermediateScale = 0.007059f;
- layerDesc.m_OutputIntermediateScale = 0.007812f;
-
- QLstmLayer* const layer = graph.AddLayer<QLstmLayer>(layerDesc, "qLstm");
-
- unsigned int numBatches = 2;
- unsigned int inputSize = 4;
- unsigned int numUnits = 4;
- unsigned int outputSize = 4;
-
- // Scale/Offset quantization info
- float inputScale = 0.0078125f;
- int32_t inputOffset = 0;
-
- // if (!projectionEnabled) outputScale == hiddenStateScale
- float outputScale = layerDesc.m_HiddenStateScale;
- int32_t outputOffset = layerDesc.m_HiddenStateZeroPoint;
-
- float cellStateScale = 3.05176e-05f;
- int32_t cellStateOffset = 0;
-
- float weightsScale = 0.00784314f;
- int32_t weightsOffset = 0;
-
- float layerNormScale = 3.05182e-05f;
- int32_t layerNormOffset = 0;
-
- float biasScale = layerNormScale / 1024;
- int32_t biasOffset = 0;
-
- // Weights and bias tensor and quantization info
- armnn::TensorInfo inputWeightsInfo({outputSize, inputSize},
- armnn::DataType::QSymmS8,
- weightsScale,
- weightsOffset);
-
- armnn::TensorInfo recurrentWeightsInfo({outputSize, outputSize},
- armnn::DataType::QSymmS8,
- weightsScale,
- weightsOffset);
-
- armnn::TensorInfo biasInfo({outputSize}, armnn::DataType::Signed32, biasScale, biasOffset);
-
- armnn::TensorInfo layerNormWeightsInfo({numUnits}, armnn::DataType::QSymmS16, layerNormScale, layerNormOffset);
-
- // Create and allocate tensors
- layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
- layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
- layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
-
- layer->m_BasicParameters.m_RecurrentToForgetWeights =
- std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
- layer->m_BasicParameters.m_RecurrentToCellWeights =
- std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
- layer->m_BasicParameters.m_RecurrentToOutputWeights =
- std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
-
- layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);
- layer->m_BasicParameters.m_CellBias = std::make_unique<ScopedTensorHandle>(biasInfo);
- layer->m_BasicParameters.m_OutputGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);
-
- layer->m_LayerNormParameters.m_ForgetLayerNormWeights =
- std::make_unique<ScopedTensorHandle>(layerNormWeightsInfo);
- layer->m_LayerNormParameters.m_CellLayerNormWeights =
- std::make_unique<ScopedTensorHandle>(layerNormWeightsInfo);
- layer->m_LayerNormParameters.m_OutputLayerNormWeights =
- std::make_unique<ScopedTensorHandle>(layerNormWeightsInfo);
-
- layer->m_BasicParameters.m_InputToForgetWeights->Allocate();
- layer->m_BasicParameters.m_InputToCellWeights->Allocate();
- layer->m_BasicParameters.m_InputToOutputWeights->Allocate();
-
- layer->m_BasicParameters.m_RecurrentToForgetWeights->Allocate();
- layer->m_BasicParameters.m_RecurrentToCellWeights->Allocate();
- layer->m_BasicParameters.m_RecurrentToOutputWeights->Allocate();
-
- layer->m_BasicParameters.m_ForgetGateBias->Allocate();
- layer->m_BasicParameters.m_CellBias->Allocate();
- layer->m_BasicParameters.m_OutputGateBias->Allocate();
-
- layer->m_LayerNormParameters.m_ForgetLayerNormWeights->Allocate();
- layer->m_LayerNormParameters.m_CellLayerNormWeights->Allocate();
- layer->m_LayerNormParameters.m_OutputLayerNormWeights->Allocate();
-
- // Input and output layers
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const outputStateIn = graph.AddLayer<InputLayer>(1, "outputStateIn");
- Layer* const cellStateIn = graph.AddLayer<InputLayer>(2, "cellStateIn");
-
- Layer* const outputStateOut = graph.AddLayer<OutputLayer>(0, "outputStateOut");
- Layer* const cellStateOut = graph.AddLayer<OutputLayer>(1, "cellStateOut");
- Layer* const output = graph.AddLayer<OutputLayer>(2, "output");
-
- // Input/Output tensor info
- armnn::TensorInfo inputInfo({numBatches , inputSize},
- armnn::DataType::QAsymmS8,
- inputScale,
- inputOffset);
-
- armnn::TensorInfo cellStateInfo({numBatches , numUnits},
- armnn::DataType::QSymmS16,
- cellStateScale,
- cellStateOffset);
-
- armnn::TensorInfo outputStateInfo({numBatches , outputSize},
- armnn::DataType::QAsymmS8,
- outputScale,
- outputOffset);
-
- // Connect layers to slots
- Connect(input, layer, inputInfo, 0, 0);
- Connect(outputStateIn, layer, outputStateInfo, 0, 1);
- Connect(cellStateIn, layer, cellStateInfo, 0, 2);
-
- Connect(layer, outputStateOut, outputStateInfo, 0, 0);
- Connect(layer, cellStateOut, cellStateInfo, 1, 0);
- Connect(layer, output, outputStateInfo, 2, 0);
-
- CreateTensorHandles(graph, factory);
-
- // Create and check workload
- auto workload = MakeAndCheckWorkload<QLstmWorkload>(*layer, factory);
- QLstmQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Parameters.m_CellClip == 0.0f);
- CHECK(queueDescriptor.m_Parameters.m_ProjectionClip == 0.0f);
- CHECK(queueDescriptor.m_Inputs.size() == 3);
- CHECK(queueDescriptor.m_Outputs.size() == 3);
-
- CHECK((queueDescriptor.m_InputToForgetWeights->GetTensorInfo() == inputWeightsInfo));
- CHECK((queueDescriptor.m_InputToCellWeights->GetTensorInfo() == inputWeightsInfo));
- CHECK((queueDescriptor.m_InputToOutputWeights->GetTensorInfo() == inputWeightsInfo));
-
- CHECK((queueDescriptor.m_RecurrentToForgetWeights->GetTensorInfo() == recurrentWeightsInfo));
- CHECK((queueDescriptor.m_RecurrentToCellWeights->GetTensorInfo() == recurrentWeightsInfo));
- CHECK((queueDescriptor.m_RecurrentToOutputWeights->GetTensorInfo() == recurrentWeightsInfo));
-
- CHECK((queueDescriptor.m_ForgetGateBias->GetTensorInfo() == biasInfo));
- CHECK((queueDescriptor.m_CellBias->GetTensorInfo() == biasInfo));
- CHECK((queueDescriptor.m_OutputGateBias->GetTensorInfo() == biasInfo));
-
- return workload;
-}
-
-template <typename Convolution2dWorkload, armnn::DataType DataType>
-std::unique_ptr<Convolution2dWorkload> CreateDirectConvolution2dWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- // Creates the layer we're testing.
- Convolution2dDescriptor layerDesc;
- layerDesc.m_PadLeft = 1;
- layerDesc.m_PadRight = 1;
- layerDesc.m_PadTop = 1;
- layerDesc.m_PadBottom = 1;
- layerDesc.m_StrideX = 1;
- layerDesc.m_StrideY = 1;
- layerDesc.m_BiasEnabled = true;
-
- Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");
-
- float inputsQScale = DataType == armnn::DataType::QAsymmU8 ? 1.0f : 0.0;
- float outputQScale = DataType == armnn::DataType::QAsymmU8 ? 2.0f : 0.0;
-
- layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({ 2, 3, 3, 3 }, DataType, inputsQScale));
- layer->m_Bias = std::make_unique<ScopedTensorHandle>
- (TensorInfo({2}, GetBiasDataType(DataType), inputsQScale));
- layer->m_Weight->Allocate();
- layer->m_Bias->Allocate();
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- Connect(input, layer, TensorInfo({2, 3, 6, 6}, DataType, inputsQScale));
- Connect(layer, output, TensorInfo({2, 2, 6, 6}, DataType, outputQScale));
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory);
-
- Convolution2dQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Parameters.m_StrideX == 1);
- CHECK(queueDescriptor.m_Parameters.m_StrideY == 1);
- CHECK(queueDescriptor.m_Parameters.m_PadLeft == 1);
- CHECK(queueDescriptor.m_Parameters.m_PadRight == 1);
- CHECK(queueDescriptor.m_Parameters.m_PadTop == 1);
- CHECK(queueDescriptor.m_Parameters.m_PadBottom == 1);
- CHECK(queueDescriptor.m_Parameters.m_BiasEnabled == true);
-
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
- CHECK((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo({2, 3, 3, 3},
- DataType, inputsQScale)));
- CHECK((queueDescriptor.m_Bias->GetTensorInfo()
- == TensorInfo({2}, GetBiasDataType(DataType), inputsQScale)));
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename DepthwiseConvolution2dFloat32Workload, armnn::DataType DataType>
-std::unique_ptr<DepthwiseConvolution2dFloat32Workload> CreateDepthwiseConvolution2dWorkloadTest(
- armnn::IWorkloadFactory& factory, armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW)
-{
- // Creates the layer we're testing.
- DepthwiseConvolution2dDescriptor layerDesc;
- layerDesc.m_PadLeft = 1;
- layerDesc.m_PadRight = 2;
- layerDesc.m_PadTop = 1;
- layerDesc.m_PadBottom = 2;
- layerDesc.m_StrideX = 1;
- layerDesc.m_StrideY = 1;
- layerDesc.m_BiasEnabled = false;
- layerDesc.m_DataLayout = dataLayout;
-
- DepthwiseConvolution2dLayer* const layer = graph.AddLayer<DepthwiseConvolution2dLayer>(layerDesc, "layer");
-
- layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({1, 4, 4, 2}, DataType)); // [ 1, H, W, I*M ]
- layer->m_Weight->Allocate();
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- TensorShape inputShape = (dataLayout == DataLayout::NCHW) ?
- TensorShape{ 2, 2, 5, 5 } : TensorShape{ 2, 5, 5, 2 };
- TensorShape outputShape = (dataLayout == DataLayout::NCHW) ?
- TensorShape{ 2, 2, 5, 5 } : TensorShape{ 2, 5, 5, 2 };
-
- // Connects up.
- Connect(input, layer, TensorInfo(inputShape, DataType));
- Connect(layer, output, TensorInfo(outputShape, DataType));
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<DepthwiseConvolution2dFloat32Workload>(*layer, factory);
-
- DepthwiseConvolution2dQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Parameters.m_StrideX == 1);
- CHECK(queueDescriptor.m_Parameters.m_StrideY == 1);
- CHECK(queueDescriptor.m_Parameters.m_PadLeft == 1);
- CHECK(queueDescriptor.m_Parameters.m_PadRight == 2);
- CHECK(queueDescriptor.m_Parameters.m_PadTop == 1);
- CHECK(queueDescriptor.m_Parameters.m_PadBottom == 2);
- CHECK(queueDescriptor.m_Parameters.m_BiasEnabled == false);
- CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
-
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
- CHECK((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo({1, 4, 4, 2}, DataType)));
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename FullyConnectedWorkload, armnn::DataType DataType>
-std::unique_ptr<FullyConnectedWorkload> CreateFullyConnectedWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- // Creates the layer we're testing.
- FullyConnectedDescriptor layerDesc;
- layerDesc.m_BiasEnabled = false;
- layerDesc.m_TransposeWeightMatrix = true;
-
- FullyConnectedLayer* const layer = graph.AddLayer<FullyConnectedLayer>(layerDesc, "layer");
-
- float inputsQScale = DataType == armnn::DataType::QAsymmU8 ? 1.0f : 0.0;
- float outputQScale = DataType == armnn::DataType::QAsymmU8 ? 2.0f : 0.0;
-
- // As optimization isn't run member variables need to be updated.
- layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({7, 20}, DataType, inputsQScale, 0));
- layer->m_Weight->Allocate();
-
- armnn::TensorInfo weightsTensorInfo({7, 20}, DataType, inputsQScale);
- weightsTensorInfo.SetConstant();
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- auto const weights = graph.AddLayer<ConstantLayer>("weights");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- weights->m_LayerOutput = std::make_unique<ScopedTensorHandle>(weightsTensorInfo);
- weights->m_LayerOutput->Allocate();
-
- // Connects up.
- Connect(input, layer, TensorInfo({3, 1, 4, 5}, DataType, inputsQScale), 0, 0);
- Connect(weights, layer, weightsTensorInfo, 0, 1);
- Connect(layer, output, TensorInfo({3, 7}, DataType, outputQScale));
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<FullyConnectedWorkload>(*layer, factory);
-
- FullyConnectedQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Parameters.m_TransposeWeightMatrix == true);
-
- CHECK(queueDescriptor.m_Inputs.size() == 2);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename FullyConnectedWorkload, armnn::DataType DataType>
-std::unique_ptr<FullyConnectedWorkload> CreateFullyConnectedWithBlobWorkloadTest
- (armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- // Creates 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 = DataType == armnn::DataType::QAsymmU8 ? 1.0f : 0.0;
- float outputQScale = DataType == armnn::DataType::QAsymmU8 ? 2.0f : 0.0;
-
- // As optimization isn't run member variables need to be updated.
- layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({7, 20}, DataType, inputsQScale, 0));
- layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({7}, GetBiasDataType(DataType), inputsQScale));
- layer->m_Weight->Allocate();
- layer->m_Bias->Allocate();
-
- armnn::TensorInfo weightsTensorInfo({7, 20}, DataType, inputsQScale);
- armnn::TensorInfo biasesTensorInfo({7}, GetBiasDataType(DataType), inputsQScale);
- weightsTensorInfo.SetConstant();
- biasesTensorInfo.SetConstant();
-
- auto activationDesc = std::make_shared<ActivationDescriptor>();
- activationDesc->m_A = 10.0f;
- activationDesc->m_B = 5.0f;
- activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
-
- layer->SetAdditionalInfoForObject(activationDesc);
-
- // Check that the additional information can be queried from the layer
- std::shared_ptr<ActivationDescriptor> activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
- ARMNN_ASSERT(static_cast<ActivationFunction>(activationDescPtr->m_Function) ==
- armnn::ActivationFunction::BoundedReLu);
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- auto const weights = graph.AddLayer<ConstantLayer>("weights");
- auto const biases = graph.AddLayer<ConstantLayer>("biases");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- weights->m_LayerOutput = std::make_unique<ScopedTensorHandle>(weightsTensorInfo);
- weights->m_LayerOutput->Allocate();
- biases->m_LayerOutput = std::make_unique<ScopedTensorHandle>(biasesTensorInfo);
- biases->m_LayerOutput->Allocate();
-
- // Connects up.
- Connect(input, layer, TensorInfo({3, 1, 4, 5}, DataType, inputsQScale), 0, 0);
- Connect(weights, layer, weightsTensorInfo, 0, 1);
- Connect(biases, layer, biasesTensorInfo, 0, 2);
- Connect(layer, output, TensorInfo({3, 7}, DataType, outputQScale));
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<FullyConnectedWorkload>(*layer, factory);
-
- FullyConnectedQueueDescriptor queueDescriptor = workload->GetData();
-
- const ActivationDescriptor* queueDescBlobPtr = queueDescriptor.GetAdditionalInformation<ActivationDescriptor>();
- IgnoreUnused(queueDescBlobPtr);
-
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
- ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
- ARMNN_ASSERT(
- static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
- );
-
- CHECK(queueDescriptor.m_Parameters.m_BiasEnabled == true);
- CHECK(queueDescriptor.m_Parameters.m_TransposeWeightMatrix == true);
- CHECK(queueDescriptor.m_Inputs.size() == 3);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename FullyConnectedWorkload, armnn::DataType DataType>
-std::unique_ptr<FullyConnectedWorkload> CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest
- (armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- // Creates the layer we're testing.
- FullyConnectedDescriptor layerDesc;
- layerDesc.m_BiasEnabled = true;
- layerDesc.m_TransposeWeightMatrix = true;
- layerDesc.m_ConstantWeights = false;
-
- FullyConnectedLayer* const layer = graph.AddLayer<FullyConnectedLayer>(layerDesc, "layer");
-
- float inputsQScale = DataType == armnn::DataType::QAsymmU8 ? 1.0f : 0.0;
- float outputQScale = DataType == armnn::DataType::QAsymmU8 ? 2.0f : 0.0;
-
- // Creates extra layers with weights and biases as input layers.
- Layer* const input = graph.AddLayer<InputLayer>(1, "input");
- Layer* const weights = graph.AddLayer<InputLayer>(2, "weights");
- Layer* const biases = graph.AddLayer<InputLayer>(3, "biases");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- Connect(input, layer, TensorInfo({3, 1, 4, 5}, DataType, inputsQScale), 0, 0);
- Connect(weights, layer, TensorInfo({7, 20}, DataType, inputsQScale), 0, 1);
- Connect(biases, layer, TensorInfo({7}, GetBiasDataType(DataType), inputsQScale), 0, 2);
- Connect(layer, output, TensorInfo({3, 7}, DataType, outputQScale));
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<FullyConnectedWorkload>(*layer, factory);
-
- FullyConnectedQueueDescriptor queueDescriptor = workload->GetData();
-
- CHECK(queueDescriptor.m_Parameters.m_BiasEnabled == true);
- CHECK(queueDescriptor.m_Parameters.m_TransposeWeightMatrix == true);
- CHECK(queueDescriptor.m_Parameters.m_ConstantWeights == false);
- CHECK(queueDescriptor.m_Inputs.size() == 3);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-
-template <typename NormalizationWorkload, armnn::DataType DataType>
-std::unique_ptr<NormalizationWorkload> CreateNormalizationWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph,
- DataLayout dataLayout = DataLayout::NCHW)
-{
- // Creates the layer we're testing.
- NormalizationDescriptor layerDesc;
- layerDesc.m_NormChannelType = NormalizationAlgorithmChannel::Across;
- layerDesc.m_NormMethodType = NormalizationAlgorithmMethod::LocalBrightness;
- layerDesc.m_NormSize = 3;
- layerDesc.m_Alpha = 0.5f;
- layerDesc.m_Beta = -1.0f;
- layerDesc.m_K = 0.2f;
- layerDesc.m_DataLayout = dataLayout;
-
- NormalizationLayer* layer = graph.AddLayer<NormalizationLayer>(layerDesc, "layer");
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- TensorShape inputShape = (dataLayout == DataLayout::NCHW) ?
- TensorShape{ 3, 5, 5, 1 } : TensorShape{ 3, 1, 5, 5 };
- TensorShape outputShape = (dataLayout == DataLayout::NCHW) ?
- TensorShape{ 3, 5, 5, 1 } : TensorShape{ 3, 1, 5, 5 };
-
- // Connects up.
- armnn::TensorInfo inputTensorInfo(inputShape, DataType);
- armnn::TensorInfo outputTensorInfo(outputShape, DataType);
- Connect(input, layer, inputTensorInfo);
- Connect(layer, output, outputTensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<NormalizationWorkload>(*layer, factory);
-
- NormalizationQueueDescriptor queueDescriptor = workload->GetData();
- CHECK((queueDescriptor.m_Parameters.m_NormChannelType == NormalizationAlgorithmChannel::Across));
- CHECK((queueDescriptor.m_Parameters.m_NormMethodType == NormalizationAlgorithmMethod::LocalBrightness));
- CHECK(queueDescriptor.m_Parameters.m_NormSize == 3);
- CHECK(queueDescriptor.m_Parameters.m_Alpha == 0.5f);
- CHECK(queueDescriptor.m_Parameters.m_Beta == -1.0f);
- CHECK(queueDescriptor.m_Parameters.m_K == 0.2f);
- CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
-
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename Pooling2dWorkload, armnn::DataType DataType>
-std::unique_ptr<Pooling2dWorkload> CreatePooling2dWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph,
- DataLayout dataLayout = DataLayout::NCHW)
-{
- // Creates the layer we're testing.
- Pooling2dDescriptor layerDesc;
- layerDesc.m_PoolType = PoolingAlgorithm::Average;
- layerDesc.m_PoolWidth = 3;
- layerDesc.m_PoolHeight = 3;
- layerDesc.m_PadLeft = 2;
- layerDesc.m_PadRight = 2;
- layerDesc.m_PadTop = 1;
- layerDesc.m_PadBottom = 1;
- layerDesc.m_StrideX = 2;
- layerDesc.m_StrideY = 3;
- layerDesc.m_OutputShapeRounding = OutputShapeRounding::Floor;
- layerDesc.m_DataLayout = dataLayout;
-
- Pooling2dLayer* const layer = graph.AddLayer<Pooling2dLayer>(layerDesc, "layer");
-
- // Create extra layers
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{3, 2, 5, 5} : TensorShape{3, 5, 5, 2};
- TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{3, 2, 2, 4} : TensorShape{3, 2, 4, 2};
-
- // Connect up
- Connect(input, layer, TensorInfo(inputShape, DataType));
- Connect(layer, output, TensorInfo(outputShape, DataType));
- CreateTensorHandles(graph, factory);
-
- // Make the workload and checks it
- auto workload = MakeAndCheckWorkload<Pooling2dWorkload>(*layer, factory);
-
- Pooling2dQueueDescriptor queueDescriptor = workload->GetData();
- CHECK((queueDescriptor.m_Parameters.m_PoolType == PoolingAlgorithm::Average));
- CHECK((queueDescriptor.m_Parameters.m_OutputShapeRounding == OutputShapeRounding::Floor));
- CHECK(queueDescriptor.m_Parameters.m_PoolWidth == 3);
- CHECK(queueDescriptor.m_Parameters.m_PoolHeight == 3);
- CHECK(queueDescriptor.m_Parameters.m_StrideX == 2);
- CHECK(queueDescriptor.m_Parameters.m_StrideY == 3);
- CHECK(queueDescriptor.m_Parameters.m_PadLeft == 2);
- CHECK(queueDescriptor.m_Parameters.m_PadRight == 2);
- CHECK(queueDescriptor.m_Parameters.m_PadTop == 1);
- CHECK(queueDescriptor.m_Parameters.m_PadBottom == 1);
- CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
-
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Return so we can do extra, backend-specific tests
- return workload;
-}
-
-template <typename SoftmaxWorkload, armnn::DataType DataType>
-std::unique_ptr<SoftmaxWorkload> CreateSoftmaxWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- // Create the layer we're testing.
- SoftmaxDescriptor softmaxDescriptor;
- // Set Axis to -1 if CL or Neon until further Axes are supported.
- if (factory.GetBackendId() == armnn::Compute::CpuAcc || factory.GetBackendId() == armnn::Compute::GpuAcc)
- {
- softmaxDescriptor.m_Axis = -1;
- }
-
- Layer* const layer = graph.AddLayer<SoftmaxLayer>(softmaxDescriptor, "layer");
- // Create extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connect up
- armnn::TensorInfo tensorInfo({4, 1}, DataType);
- if (DataType == armnn::DataType::QAsymmU8)
- {
- tensorInfo.SetQuantizationOffset(0);
- tensorInfo.SetQuantizationScale(1.f / 256);
- }
- else if (DataType == armnn::DataType::QAsymmS8)
- {
- tensorInfo.SetQuantizationOffset(-128);
- tensorInfo.SetQuantizationScale(1.f / 256);
- }
-
- Connect(input, layer, tensorInfo);
- Connect(layer, output, tensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Make the workload and checks it.
- auto workload = MakeAndCheckWorkload<SoftmaxWorkload>(*layer, factory);
-
- SoftmaxQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Return so we can do extra, backend-specific tests.
- return workload;
-}
-
-template<typename SplitterWorkload, armnn::DataType DataType>
-std::unique_ptr<SplitterWorkload>
- CreateSplitterWorkloadTest(armnn::IWorkloadFactory& factory, armnn::Graph& graph)
-{
- // Create the layer we're testing.
- // NOTE: need three dimensions channels, height/y, width/x because the Compute
- // library restricts subtensors to have the same x and y dimensions as
- // their parent tensors, and therefore the origin on the x and y dimension
- // has to be zero for any view. So we need a third dimension to split...
- // NOTE: arguments are: number of views, number of dimensions.
- ViewsDescriptor layerDesc(3, 3);
- // NOTE: arguments are: view, dimension, value.
- layerDesc.SetViewOriginCoord(0, 0, 0);
- layerDesc.SetViewOriginCoord(1, 0, 1);
- layerDesc.SetViewOriginCoord(2, 0, 3);
-
- Layer* const layer = graph.AddLayer<SplitterLayer>(layerDesc, "layer");
-
- // Adds extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output0 = graph.AddLayer<OutputLayer>(0, "output0");
- Layer* const output1 = graph.AddLayer<OutputLayer>(1, "output1");
- Layer* const output2 = graph.AddLayer<OutputLayer>(2, "output2");
-
- // Connects up.
- armnn::TensorInfo tensorInfo({5, 7, 7}, DataType);
- Connect(input, layer, tensorInfo);
-
- armnn::TensorInfo output0Info({1, 7, 7}, DataType);
- armnn::TensorInfo output1Info({2, 7, 7}, DataType);
- armnn::TensorInfo output2Info({2, 7, 7}, DataType);
-
- Connect(layer, output0, output0Info, 0, 0);
- Connect(layer, output1, output1Info, 1, 0);
- Connect(layer, output2, output2Info, 2, 0);
-
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<SplitterWorkload>(*layer, factory);
-
- SplitterQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 3);
- CHECK(queueDescriptor.m_ViewOrigins.size() == 3);
-
- CHECK(queueDescriptor.m_ViewOrigins[0].m_Origin[0] == 0);
- CHECK(queueDescriptor.m_ViewOrigins[1].m_Origin[0] == 1);
- CHECK(queueDescriptor.m_ViewOrigins[2].m_Origin[0] == 3);
- CHECK(queueDescriptor.m_ViewOrigins[0].m_Origin[1] == 0);
- CHECK(queueDescriptor.m_ViewOrigins[1].m_Origin[1] == 0);
- CHECK(queueDescriptor.m_ViewOrigins[2].m_Origin[1] == 0);
- CHECK(queueDescriptor.m_ViewOrigins[0].m_Origin[2] == 0);
- CHECK(queueDescriptor.m_ViewOrigins[1].m_Origin[2] == 0);
- CHECK(queueDescriptor.m_ViewOrigins[2].m_Origin[2] == 0);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-/// This function constructs a graph with both a splitter and a concat, and returns a pair of the workloads.
-template<typename SplitterWorkload, typename ConcatWorkload, armnn::DataType DataType>
-std::pair<std::unique_ptr<SplitterWorkload>, std::unique_ptr<ConcatWorkload>>
- CreateSplitterConcatWorkloadTest(armnn::IWorkloadFactory &factory, armnn::Graph &graph)
-{
- armnn::TensorInfo inputTensorInfo({ 1, 2, 100, 10 }, DataType);
-
- armnn::TensorInfo splitTensorInfo1({ 1, 1, 100, 10 }, DataType);
- armnn::TensorInfo splitTensorInfo2({ 1, 1, 100, 10 }, DataType);
-
- //Constructs the graph.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
-
- armnn::ViewsDescriptor splitterViews(2);
- splitterViews.SetViewOriginCoord(0, 0, 0);
- splitterViews.SetViewOriginCoord(0, 1, 0);
- splitterViews.SetViewOriginCoord(0, 2, 0);
- splitterViews.SetViewOriginCoord(0, 3, 0);
-
- splitterViews.SetViewOriginCoord(1, 0, 0);
- splitterViews.SetViewOriginCoord(1, 1, 1);
- splitterViews.SetViewOriginCoord(1, 2, 0);
- splitterViews.SetViewOriginCoord(1, 3, 0);
-
- // create splitter layer
- Layer* const splitter = graph.AddLayer<SplitterLayer>(splitterViews, "splitter");
- CHECK(splitter);
-
- armnn::OriginsDescriptor concatViews(2);
- concatViews.SetViewOriginCoord(0, 0, 0);
- concatViews.SetViewOriginCoord(0, 1, 1);
- concatViews.SetViewOriginCoord(0, 2, 0);
- concatViews.SetViewOriginCoord(0, 3, 0);
-
- concatViews.SetViewOriginCoord(1, 0, 0);
- concatViews.SetViewOriginCoord(1, 1, 0);
- concatViews.SetViewOriginCoord(1, 2, 0);
- concatViews.SetViewOriginCoord(1, 3, 0);
-
- // create concat layer
- Layer* const concat = graph.AddLayer<ConcatLayer>(concatViews, "concat");
- CHECK(concat);
-
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Adds connections.
- // connect input to splitter
- Connect(input, splitter, inputTensorInfo, 0, 0);
- // connect splitter[0] to concat[1]
- Connect(splitter, concat, splitTensorInfo1, 0, 1); // The splitter & concat are connected up.
- // connect splitter[1] to concat[0]
- Connect(splitter, concat, splitTensorInfo2, 1, 0); // So that the outputs are flipped round.
- // connect concat to output
- Connect(concat, output, inputTensorInfo, 0, 0);
-
- // created tensor handles
- CreateTensorHandles(graph, factory);
-
- // created splitter workload
- auto workloadSplitter = MakeAndCheckWorkload<SplitterWorkload>(*splitter, factory);
- CHECK(workloadSplitter);
- // created concat workload
- auto workloadConcat = MakeAndCheckWorkload<ConcatWorkload>(*concat, factory);
- CHECK(workloadConcat);
-
- return {std::move(workloadSplitter), std::move(workloadConcat)};
-}
-
-
-/// This function constructs a graph with a splitter with two outputs. Each of the outputs is then
-/// connected to two different activation layers
-template<typename SplitterWorkload, typename ActivationWorkload, armnn::DataType DataType>
-void CreateSplitterMultipleInputsOneOutputWorkloadTest(armnn::IWorkloadFactory& factory, armnn::Graph& graph,
- std::unique_ptr<SplitterWorkload>& wlSplitter,
- std::unique_ptr<ActivationWorkload>& wlActiv0_0,
- std::unique_ptr<ActivationWorkload>& wlActiv0_1,
- std::unique_ptr<ActivationWorkload>& wlActiv1_0,
- std::unique_ptr<ActivationWorkload>& wlActiv1_1)
-{
- armnn::TensorInfo inputTensorInfo ({ 1, 3, 100, 50 }, DataType);
- armnn::TensorInfo splitTensorInfo1({ 1, 1, 100, 50 }, DataType);
- armnn::TensorInfo splitTensorInfo2({ 1, 2, 100, 50 }, DataType);
-
- //Constructs the graph.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
-
- armnn::ViewsDescriptor splitterViews(2);
-
- splitterViews.SetViewOriginCoord(0, 0, 0);
- splitterViews.SetViewOriginCoord(0, 1, 0);
- splitterViews.SetViewOriginCoord(0, 2, 0);
- splitterViews.SetViewOriginCoord(0, 3, 0);
-
- splitterViews.SetViewOriginCoord(1, 0, 0);
- splitterViews.SetViewOriginCoord(1, 1, 1);
- splitterViews.SetViewOriginCoord(1, 2, 0);
- splitterViews.SetViewOriginCoord(1, 3, 0);
-
- Layer* const splitter = graph.AddLayer<SplitterLayer>(splitterViews, "splitter");
-
- armnn::ActivationDescriptor activationDesc;
-
- Layer* const activ0_0 = graph.AddLayer<ActivationLayer>(activationDesc, "activ0_0");
- Layer* const activ0_1 = graph.AddLayer<ActivationLayer>(activationDesc, "activ0_1");
- Layer* const activ1_0 = graph.AddLayer<ActivationLayer>(activationDesc, "activ1_0");
- Layer* const activ1_1 = graph.AddLayer<ActivationLayer>(activationDesc, "activ1_1");
-
- Layer* const output1 = graph.AddLayer<OutputLayer>(1, "output1");
- Layer* const output2 = graph.AddLayer<OutputLayer>(2, "output2");
- Layer* const output3 = graph.AddLayer<OutputLayer>(3, "output3");
- Layer* const output4 = graph.AddLayer<OutputLayer>(4, "output4");
-
- // Adds connections.
- Connect(input, splitter, inputTensorInfo, 0, 0);
- Connect(splitter, activ0_0, splitTensorInfo1, 0, 0);
- Connect(splitter, activ0_1, splitTensorInfo1, 0, 0);
-
- Connect(splitter, activ1_0, splitTensorInfo2, 1, 0);
- Connect(splitter, activ1_1, splitTensorInfo2, 1, 0);
-
- Connect(activ0_0, output1, splitTensorInfo1, 0, 0);
- Connect(activ0_1, output2, splitTensorInfo1, 0, 0);
- Connect(activ1_0, output3, splitTensorInfo2, 0, 0);
- Connect(activ1_1, output4, splitTensorInfo2, 0, 0);
-
- CreateTensorHandles(graph, factory);
-
- auto workloadSplitter = MakeAndCheckWorkload<SplitterWorkload>(*splitter, factory);
- auto workloadActiv0_0 = MakeAndCheckWorkload<ActivationWorkload>(*activ0_0, factory);
- auto workloadActiv0_1 = MakeAndCheckWorkload<ActivationWorkload>(*activ0_1, factory);
- auto workloadActiv1_0 = MakeAndCheckWorkload<ActivationWorkload>(*activ1_0, factory);
- auto workloadActiv1_1 = MakeAndCheckWorkload<ActivationWorkload>(*activ1_1, factory);
-
- wlSplitter = std::move(workloadSplitter);
- wlActiv0_0 = std::move(workloadActiv0_0);
- wlActiv0_1 = std::move(workloadActiv0_1);
- wlActiv1_0 = std::move(workloadActiv1_0);
- wlActiv1_1 = std::move(workloadActiv1_1);
-}
-
-template <typename ResizeWorkload, armnn::DataType DataType>
-std::unique_ptr<ResizeWorkload> CreateResizeBilinearWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph,
- DataLayout dataLayout = DataLayout::NCHW)
-{
- TensorShape inputShape;
- TensorShape outputShape;
-
- switch (dataLayout) {
- case DataLayout::NHWC:
- inputShape = { 2, 4, 4, 3 };
- outputShape = { 2, 2, 2, 3 };
- break;
- case DataLayout::NCHW:
- default:
- inputShape = { 2, 3, 4, 4 };
- outputShape = { 2, 3, 2, 2 };
- }
-
- // Creates the layer we're testing.
- ResizeDescriptor resizeDesc;
- armnnUtils::DataLayoutIndexed dimensionIndices = dataLayout;
- resizeDesc.m_Method = ResizeMethod::Bilinear;
- resizeDesc.m_TargetWidth = outputShape[dimensionIndices.GetWidthIndex()];
- resizeDesc.m_TargetHeight = outputShape[dimensionIndices.GetHeightIndex()];
- resizeDesc.m_DataLayout = dataLayout;
- Layer* const layer = graph.AddLayer<ResizeLayer>(resizeDesc, "resize");
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo inputTensorInfo(inputShape, DataType);
- armnn::TensorInfo outputTensorInfo(outputShape, DataType);
- Connect(input, layer, inputTensorInfo);
- Connect(layer, output, outputTensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<ResizeWorkload>(*layer, factory);
-
- auto queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
- CHECK(queueDescriptor.m_Parameters.m_DataLayout == dataLayout);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename BatchToSpaceNdWorkload, armnn::DataType DataType>
-std::unique_ptr<BatchToSpaceNdWorkload> CreateBatchToSpaceNdWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- BatchToSpaceNdDescriptor desc;
- Layer* const layer = graph.AddLayer<BatchToSpaceNdLayer>(desc, "batchToSpace");
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo tensorInfo({1, 1, 1, 1}, DataType);
-
- Connect(input, layer, tensorInfo);
- Connect(layer, output, tensorInfo);
-
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<BatchToSpaceNdWorkload>(*layer, factory);
-
- BatchToSpaceNdQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- return workload;
-}
-
-template <typename LogSoftmaxWorkload, armnn::DataType DataType>
-std::unique_ptr<LogSoftmaxWorkload> CreateLogSoftmaxWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- // Create the layer we're testing.
- LogSoftmaxDescriptor logSoftmaxDescriptor;
- // Set Axis to -1 if CL or Neon until further Axes are supported.
- if (factory.GetBackendId() == armnn::Compute::CpuAcc || factory.GetBackendId() == armnn::Compute::GpuAcc)
- {
- logSoftmaxDescriptor.m_Axis = -1;
- }
-
- Layer* const layer = graph.AddLayer<LogSoftmaxLayer>(logSoftmaxDescriptor, "layer");
- // Create extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connect up
- armnn::TensorInfo tensorInfo({4, 1}, DataType);
-
- Connect(input, layer, tensorInfo);
- Connect(layer, output, tensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Make the workload and checks it.
- auto workload = MakeAndCheckWorkload<LogSoftmaxWorkload>(*layer, factory);
-
- LogSoftmaxQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Return so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename L2NormalizationWorkload, armnn::DataType DataType>
-std::unique_ptr<L2NormalizationWorkload> CreateL2NormalizationWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW)
-{
- // Creates the layer we're testing.
- L2NormalizationDescriptor layerDesc;
- layerDesc.m_DataLayout = dataLayout;
-
- Layer* const layer = graph.AddLayer<L2NormalizationLayer>(layerDesc, "l2norm");
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- TensorShape inputShape = (dataLayout == DataLayout::NCHW) ?
- TensorShape{ 5, 20, 50, 67 } : TensorShape{ 5, 50, 67, 20 };
- TensorShape outputShape = (dataLayout == DataLayout::NCHW) ?
- TensorShape{ 5, 20, 50, 67 } : TensorShape{ 5, 50, 67, 20 };
-
- // Connects up.
- armnn::TensorInfo inputTensorInfo(inputShape, DataType);
- armnn::TensorInfo outputTensorInfo(outputShape, DataType);
- Connect(input, layer, inputTensorInfo);
- Connect(layer, output, outputTensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<L2NormalizationWorkload>(*layer, factory);
-
- L2NormalizationQueueDescriptor queueDescriptor = workload->GetData();
- CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename ReshapeWorkload, armnn::DataType DataType>
-std::unique_ptr<ReshapeWorkload> CreateReshapeWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- // Creates the layer we're testing.
- TensorShape outputShape({ 1, 4 });
- ReshapeDescriptor reshapeDesc;
- reshapeDesc.m_TargetShape = outputShape;
- Layer* const layer = graph.AddLayer<ReshapeLayer>(reshapeDesc, "layer");
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo inputTensorInfo({ 4, 1 }, DataType);
- armnn::TensorInfo outputTensorInfo(outputShape, DataType);
- Connect(input, layer, inputTensorInfo);
- Connect(layer, output, outputTensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<ReshapeWorkload>(*layer, factory);
-
- ReshapeQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename ConvertFp16ToFp32Float32Workload>
-std::unique_ptr<ConvertFp16ToFp32Float32Workload> CreateConvertFp16ToFp32WorkloadTest(
- armnn::IWorkloadFactory& factory, armnn::Graph& graph)
-{
- // Creates the layer we're testing.
- ConvertFp16ToFp32Layer* const layer = graph.AddLayer<ConvertFp16ToFp32Layer>("Fp16ToFp32Converter");
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo inputTensorInfo({1, 3, 2, 3}, armnn::DataType::Float16);
- armnn::TensorInfo outputTensorInfo({1, 3, 2, 3}, armnn::DataType::Float32);
- Connect(input, layer, inputTensorInfo);
- Connect(layer, output, outputTensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<ConvertFp16ToFp32Float32Workload>(*layer, factory);
-
- ConvertFp16ToFp32QueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename ConvertFp32ToFp16Float16Workload>
-std::unique_ptr<ConvertFp32ToFp16Float16Workload> CreateConvertFp32ToFp16WorkloadTest(
- armnn::IWorkloadFactory& factory, armnn::Graph& graph)
-{
- // Creates the layer we're testing.
- ConvertFp32ToFp16Layer* const layer = graph.AddLayer<ConvertFp32ToFp16Layer>("Fp32ToFp16Converter");
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo inputTensorInfo({1, 3, 2, 3}, armnn::DataType::Float32);
- armnn::TensorInfo outputTensorInfo({1, 3, 2, 3}, armnn::DataType::Float16);
- Connect(input, layer, inputTensorInfo);
- Connect(layer, output, outputTensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<ConvertFp32ToFp16Float16Workload>(*layer, factory);
-
- ConvertFp32ToFp16QueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename MeanWorkload, armnn::DataType DataType>
-std::unique_ptr<MeanWorkload> CreateMeanWorkloadTest(armnn::IWorkloadFactory& factory, armnn::Graph& graph)
-{
- // Reduce along the first and second dimensions, and do not keep the reduced dimensions.
- MeanDescriptor descriptor({ 1, 2 }, false);
-
- // Creates the layer we're testing.
- Layer* const layer = graph.AddLayer<MeanLayer>(descriptor, "mean");
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo inputTensorInfo({ 1, 3, 7, 4 }, DataType);
- armnn::TensorInfo outputTensorInfo({ 1, 4 }, DataType);
- Connect(input, layer, inputTensorInfo);
- Connect(layer, output, outputTensorInfo);
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<MeanWorkload>(*layer, factory);
-
- MeanQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Parameters.m_Axis == descriptor.m_Axis);
- CHECK(queueDescriptor.m_Parameters.m_KeepDims == descriptor.m_KeepDims);
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template<typename ConcatWorkload, armnn::DataType DataType>
-std::unique_ptr<ConcatWorkload> CreateConcatWorkloadTest(armnn::IWorkloadFactory &factory,
- armnn::Graph &graph,
- const armnn::TensorShape &outputShape,
- unsigned int concatAxis)
-{
- armnn::TensorInfo inputTensorInfo({ 2, 3, 2, 5 }, DataType);
- armnn::TensorInfo outputTensorInfo(outputShape, DataType);
-
- // Constructs the graph.
- Layer* const input0 = graph.AddLayer<InputLayer>(0, "input0");
- Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");
- armnn::OriginsDescriptor descriptor;
-
- std::vector<armnn::TensorShape> inputShapes{{ 2, 3, 2, 5 }, { 2, 3, 2, 5 }};
-
- descriptor = CreateDescriptorForConcatenation(inputShapes.begin(),
- inputShapes.end(),
- concatAxis);
-
- // create concat layer
- Layer* const concat = graph.AddLayer<ConcatLayer>(descriptor, "concat");
- CHECK(concat);
-
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Adds connections.
- // connect input0 to concat
- Connect(input0, concat, inputTensorInfo, 0, 0);
- // connect input1 to concat
- Connect(input1, concat, inputTensorInfo, 0, 1);
- // connect concat to output
- Connect(concat, output, outputTensorInfo, 0, 0);
-
- // create tensor handles
- CreateTensorHandles(graph, factory);
-
- // create concat workload
- auto workloadConcat = MakeAndCheckWorkload<ConcatWorkload>(*concat, factory);
- CHECK(workloadConcat);
-
- return workloadConcat;
-}
-
-template <typename PreCompiledWorkload, armnn::DataType dataType>
-std::pair<armnn::IOptimizedNetworkPtr, std::unique_ptr<PreCompiledWorkload>> CreatePreCompiledWorkloadTest(
- armnn::IWorkloadFactory& factory,
- armnn::Graph& graph,
- bool biasEnabled = false)
-{
- IgnoreUnused(graph);
-
- // build up the structure of the network
- armnn::INetworkPtr net(armnn::INetwork::Create());
-
- // Add an input layer
- armnn::IConnectableLayer* const inputLayer = net->AddInputLayer(0, "input layer");
- CHECK(inputLayer);
-
- // ArmNN weights tensor shape is OIHW (out channels, in channels, height, width) for NCHW
- // ArmNN weights tensor shape is OHWI (out channels, height, width, in channels) for NHWC
- // this test is using NHWC, so the weights shape is OHWI
- TensorInfo weightsTensorInfo(TensorShape({16, 1, 1, 16}), dataType, 0.9f, 0, true);
- unsigned int weightsLength = weightsTensorInfo.GetNumElements();
-
- using WeightType = armnn::ResolveType<dataType>;
- std::vector<WeightType> convWeightsData(weightsLength);
- for (unsigned int i = 0; i < weightsLength; ++i)
- {
- convWeightsData[i] = static_cast<WeightType>(i);
- }
-
- armnn::ConstTensor weights(weightsTensorInfo, convWeightsData);
-
- // Add a layer that can be used in the PreCompiled layer
- armnn::Convolution2dDescriptor convDesc2d;
- convDesc2d.m_StrideX = 1;
- convDesc2d.m_StrideY = 1;
- convDesc2d.m_BiasEnabled = biasEnabled;
- convDesc2d.m_DataLayout = armnn::DataLayout::NHWC;
-
- armnn::IConnectableLayer* convLayer = nullptr;
- const std::string convLayerName("conv layer");
-
- if (biasEnabled)
- {
- constexpr armnn::DataType biasDataType = ( dataType == armnn::DataType::QAsymmU8) ?
- armnn::DataType::Signed32 : armnn::DataType::Float32;
-
- TensorInfo biasTensorInfo(TensorShape({16}), biasDataType, 0.9f * 0.9f, 0, true);
- unsigned int biasLength = biasTensorInfo.GetNumElements();
-
- using BiasType = armnn::ResolveType<biasDataType>;
- std::vector<BiasType> biasData(biasLength);
- std::fill(biasData.begin(), biasData.end(), static_cast<BiasType>(0));
-
- armnn::ConstTensor biases(biasTensorInfo, biasData);
-
- // Create convolution layer with biases
- convLayer = net->AddConvolution2dLayer(convDesc2d,
- weights,
- Optional<ConstTensor>(biases),
- convLayerName.c_str());
- }
- else
- {
- // Create convolution layer without biases
- convLayer = net->AddConvolution2dLayer(convDesc2d,
- weights,
- EmptyOptional(),
- convLayerName.c_str());
- }
-
- CHECK(convLayer);
-
- // Add an output layer
- armnn::IConnectableLayer* const outputLayer = net->AddOutputLayer(0, "output layer");
- CHECK(outputLayer);
-
- // set the tensors in the network (NHWC format)
- TensorInfo inputTensorInfo(TensorShape({ 1, 16, 16, 16 }), dataType);
- if (dataType == armnn::DataType::QAsymmU8)
- {
- inputTensorInfo.SetQuantizationOffset(0);
- inputTensorInfo.SetQuantizationScale(0.9f);
- }
-
- TensorInfo outputTensorInfo(TensorShape({1, 16, 16, 16}), dataType);
- if (dataType == armnn::DataType::QAsymmU8)
- {
- outputTensorInfo.SetQuantizationOffset(0);
- outputTensorInfo.SetQuantizationScale(0.9f);
- }
-
- // Connect the layers
- inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
-
- convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- convLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
- // Optimize the network for the backend supported by the factory
- std::vector<armnn::BackendId> backends = {factory.GetBackendId()};
- armnn::IRuntime::CreationOptions options;
- armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options));
- armnn::OptimizerOptions optimizerOptions;
- armnn::IOptimizedNetworkPtr optimizedNet = armnn::Optimize(*net, backends, runtime->GetDeviceSpec(),
- optimizerOptions);
- CHECK(optimizedNet != nullptr);
-
- // Find the PreCompiled layer in the optimised graph
- armnn::Graph& optimisedGraph = GetGraphForTesting(optimizedNet.get());
- Layer* preCompiledLayer = nullptr;
- for (auto& layer : optimisedGraph)
- {
- if (layer->GetType() == LayerType::PreCompiled)
- {
- preCompiledLayer = layer;
- }
- }
- CHECK(preCompiledLayer != nullptr);
-
- // Create the TensorHandles.
- CreateTensorHandles(optimisedGraph, factory);
-
- // Make the workload and check it.
- auto workload = MakeAndCheckWorkload<PreCompiledWorkload>(*preCompiledLayer, factory);
-
- PreCompiledQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns the workload so we can do extra, backend-specific tests.
- // NOTE: We need to return the optimised network as well, otherwise it gets
- // out of scope and the tensor handles get destructed
- return std::make_pair(std::move(optimizedNet), std::move(workload));
-}
-
-template<typename ConstantWorkload, armnn::DataType DataType>
-std::unique_ptr<ConstantWorkload> CreateConstantWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph,
- const armnn::TensorShape& outputShape)
-{
- armnn::TensorInfo outputTensorInfo(outputShape, DataType);
-
- // create constant layer
- auto constant = graph.AddLayer<ConstantLayer>("constant");
- CHECK(constant);
- constant->m_LayerOutput = std::make_unique<ScopedTensorHandle>(outputTensorInfo);
-
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Adds connections.
- // connect constant to output
- Connect(constant, output, outputTensorInfo, 0, 0);
-
- // create tensor handles
- CreateTensorHandles(graph, factory);
-
- // create Constant workload"
- auto workloadConstant = MakeAndCheckWorkload<ConstantWorkload>(*constant, factory);
- CHECK(workloadConstant);
-
- return workloadConstant;
-}
-
-template <typename PreluWorkload>
-std::unique_ptr<PreluWorkload> CreatePreluWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph,
- const armnn::TensorShape& inputShape,
- const armnn::TensorShape& alphaShape,
- const armnn::TensorShape& outputShape,
- armnn::DataType dataType)
-{
- // Creates the PReLU layer
- Layer* const layer = graph.AddLayer<PreluLayer>("prelu");
- CHECK(layer != nullptr);
-
- // Creates extra layers
- Layer* const input = graph.AddLayer<InputLayer> (0, "input");
- Layer* const alpha = graph.AddLayer<InputLayer> (1, "alpha");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
- CHECK(input != nullptr);
- CHECK(alpha != nullptr);
- CHECK(output != nullptr);
-
- // Connects up
- armnn::TensorInfo inputTensorInfo (inputShape, dataType);
- armnn::TensorInfo alphaTensorInfo (alphaShape, dataType);
- armnn::TensorInfo outputTensorInfo(outputShape, dataType);
- Connect(input, layer, inputTensorInfo, 0, 0);
- Connect(alpha, layer, alphaTensorInfo, 0, 1);
- Connect(layer, output, outputTensorInfo, 0, 0);
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it
- auto workload = MakeAndCheckWorkload<PreluWorkload>(*layer, factory);
-
- PreluQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 2);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- // Returns so we can do extra, backend-specific tests.
- return workload;
-}
-
-template <typename SpaceToDepthWorkload, armnn::DataType DataType>
-std::unique_ptr<SpaceToDepthWorkload> CreateSpaceToDepthWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph)
-{
- SpaceToDepthDescriptor desc;
- desc.m_BlockSize = 2;
- Layer* const layer = graph.AddLayer<SpaceToDepthLayer>(desc, "spaceToDepth");
-
- // Creates extra layers.
- Layer* const input = graph.AddLayer<InputLayer>(0, "input");
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
-
- // Connects up.
- armnn::TensorInfo inputTensorInfo({ 1, 2, 2, 1 }, DataType);
- armnn::TensorInfo outputTensorInfo({ 1, 1, 1, 4 }, DataType);
-
- Connect(input, layer, inputTensorInfo);
- Connect(layer, output, outputTensorInfo);
-
- CreateTensorHandles(graph, factory);
-
- // Makes the workload and checks it.
- auto workload = MakeAndCheckWorkload<SpaceToDepthWorkload>(*layer, factory);
-
- SpaceToDepthQueueDescriptor queueDescriptor = workload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == 1);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- return workload;
-}
-
-template <typename StackWorkload, armnn::DataType DataType>
-std::unique_ptr<StackWorkload> CreateStackWorkloadTest(armnn::IWorkloadFactory& factory,
- armnn::Graph& graph,
- const armnn::TensorShape& inputShape,
- const armnn::TensorShape& outputShape,
- unsigned int axis,
- unsigned int numInputs)
-{
- armnn::TensorInfo inputTensorInfo(inputShape, DataType);
- armnn::TensorInfo outputTensorInfo(outputShape, DataType);
-
- // Constructs the Stack layer.
- armnn::StackDescriptor descriptor(axis, numInputs, inputShape);
- Layer* const stackLayer = graph.AddLayer<StackLayer>(descriptor, "stack");
- CHECK(stackLayer != nullptr);
-
- // Constructs layer inputs and output.
- std::vector<Layer*> inputs;
- for (unsigned int i=0; i<numInputs; ++i)
- {
- inputs.push_back(graph.AddLayer<InputLayer>(
- static_cast<int>(i),
- ("input" + std::to_string(i)).c_str()
- ));
- CHECK(inputs[i] != nullptr);
- }
- Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
- CHECK(output != nullptr);
-
- // Adds connections.
- for (unsigned int i=0; i<numInputs; ++i)
- {
- Connect(inputs[i], stackLayer, inputTensorInfo, 0, i);
- }
- Connect(stackLayer, output, outputTensorInfo, 0, 0);
-
- CreateTensorHandles(graph, factory);
-
- auto stackWorkload = MakeAndCheckWorkload<StackWorkload>(*stackLayer, factory);
- StackQueueDescriptor queueDescriptor = stackWorkload->GetData();
- CHECK(queueDescriptor.m_Inputs.size() == numInputs);
- CHECK(queueDescriptor.m_Outputs.size() == 1);
-
- return stackWorkload;
-}
-
-} // Anonymous namespace
+// This file is deprecated and will be removed soon.
+// Please use the new header in armnnTestUtils instead.
+// This will use the new armnnTestUtils header.
+#include "../../armnnTestUtils/CreateWorkload.hpp"
\ No newline at end of file
diff --git a/src/armnn/test/GraphTests.cpp b/src/armnn/test/GraphTests.cpp
index f375339..d246a08 100644
--- a/src/armnn/test/GraphTests.cpp
+++ b/src/armnn/test/GraphTests.cpp
@@ -2,7 +2,7 @@
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#include "GraphUtils.hpp"
+#include <GraphUtils.hpp>
#include <Graph.hpp>
#include <Layer.hpp>
diff --git a/src/armnn/test/GraphUtils.hpp b/src/armnn/test/GraphUtils.hpp
index 60d03dc..02954e3 100644
--- a/src/armnn/test/GraphUtils.hpp
+++ b/src/armnn/test/GraphUtils.hpp
@@ -1,25 +1,9 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
-#include <Graph.hpp>
+#include "../../armnnTestUtils/GraphUtils.hpp"
-#include <string>
-
-
-bool GraphHasNamedLayer(const armnn::Graph& graph, const std::string& name);
-
-armnn::Layer* GetFirstLayerWithName(armnn::Graph& graph, const std::string& name);
-
-bool CheckNumberOfInputSlot(armnn::Layer* layer, unsigned int num);
-
-bool CheckNumberOfOutputSlot(armnn::Layer* layer, unsigned int num);
-
-bool IsConnected(armnn::Layer* srcLayer, armnn::Layer* destLayer,
- unsigned int srcSlot, unsigned int destSlot,
- const armnn::TensorInfo& expectedTensorInfo);
-
-bool CheckOrder(const armnn::Graph& graph, const armnn::Layer* first, const armnn::Layer* second);
-
+#pragma message("src/armnn/test/GraphUtils.hpp has been deprecated, it is due for removal in 22.08 release." \
+ " Please use from armnnTestUtils library, /src/armnnTestUtils/GraphUtils.hpp)
diff --git a/src/armnn/test/InferOutputTests.cpp b/src/armnn/test/InferOutputTests.cpp
index f8d8e89..c7c0c6d 100644
--- a/src/armnn/test/InferOutputTests.cpp
+++ b/src/armnn/test/InferOutputTests.cpp
@@ -5,7 +5,7 @@
#include "InferOutputTests.hpp"
-#include <test/UnitTests.hpp>
+#include <UnitTests.hpp>
TEST_SUITE("LayerValidateOutput")
{
diff --git a/src/armnn/test/InferOutputTests.hpp b/src/armnn/test/InferOutputTests.hpp
index 6435d87..799739b 100644
--- a/src/armnn/test/InferOutputTests.hpp
+++ b/src/armnn/test/InferOutputTests.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Graph.hpp>
#include <layers/ArgMinMaxLayer.hpp>
diff --git a/src/armnn/test/NetworkTests.cpp b/src/armnn/test/NetworkTests.cpp
index c1927e3..d4edf5d 100644
--- a/src/armnn/test/NetworkTests.cpp
+++ b/src/armnn/test/NetworkTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "GraphUtils.hpp"
+#include <GraphUtils.hpp>
#include <armnn/LayerVisitorBase.hpp>
diff --git a/src/armnn/test/OptimizerTests.cpp b/src/armnn/test/OptimizerTests.cpp
index 750e696..a5db0ac 100644
--- a/src/armnn/test/OptimizerTests.cpp
+++ b/src/armnn/test/OptimizerTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "TestUtils.hpp"
+#include <TestUtils.hpp>
#include <BackendSettings.hpp>
#include <Graph.hpp>
diff --git a/src/armnn/test/PredicateResult.hpp b/src/armnn/test/PredicateResult.hpp
index a344c8e..8edf8b1 100644
--- a/src/armnn/test/PredicateResult.hpp
+++ b/src/armnn/test/PredicateResult.hpp
@@ -2,47 +2,8 @@
// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
-#include <sstream>
+#include <armnnTestUtils/PredicateResult.hpp>
-namespace armnn
-{
-
-class PredicateResult
-{
-public:
- explicit PredicateResult(bool result)
- : m_Result(result)
- {}
-
- PredicateResult(const PredicateResult& predicateResult)
- : m_Result(predicateResult.m_Result)
- , m_Message(predicateResult.m_Message.str())
- {}
-
- void SetResult(bool newResult)
- {
- m_Result = newResult;
- }
-
- std::stringstream& Message()
- {
- return m_Message;
- }
-
- bool operator!() const
- {
- return !m_Result;
- }
-
- void operator=(PredicateResult otherPredicateResult)
- {
- otherPredicateResult.m_Result = m_Result;
- }
-
- bool m_Result;
- std::stringstream m_Message;
-};
-
-} // namespace armnn
\ No newline at end of file
+#pragma message("src/armnn/test/PredicateResult.hpp has been deprecated, it is due for removal in 22.08 release." \
+ " Please use public interface include/armnnTestUtils/PredicateResult.hpp")
\ No newline at end of file
diff --git a/src/armnn/test/RuntimeTests.cpp b/src/armnn/test/RuntimeTests.cpp
index f055f23..045007b 100644
--- a/src/armnn/test/RuntimeTests.cpp
+++ b/src/armnn/test/RuntimeTests.cpp
@@ -22,7 +22,7 @@
#include <doctest/doctest.h>
#include "RuntimeTests.hpp"
-#include "TestUtils.hpp"
+#include <TestUtils.hpp>
namespace armnn
{
diff --git a/src/armnn/test/TensorHelpers.hpp b/src/armnn/test/TensorHelpers.hpp
index 95cea58..626cda3 100644
--- a/src/armnn/test/TensorHelpers.hpp
+++ b/src/armnn/test/TensorHelpers.hpp
@@ -1,235 +1,9 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
-#include "PredicateResult.hpp"
-
-#include <armnn/Tensor.hpp>
-#include <armnn/utility/Assert.hpp>
-#include <armnnUtils/FloatingPointComparison.hpp>
-
-#include <QuantizeHelper.hpp>
-
-#include <doctest/doctest.h>
-
-#include <array>
-#include <cmath>
-#include <random>
-#include <vector>
-
-constexpr float g_FloatCloseToZeroTolerance = 1.0e-6f;
-
-template<typename T, bool isQuantized = true>
-struct SelectiveComparer
-{
- static bool Compare(T a, T b)
- {
- return (std::max(a, b) - std::min(a, b)) <= 1;
- }
-
-};
-
-template<typename T>
-struct SelectiveComparer<T, false>
-{
- static bool Compare(T a, T b)
- {
- // If a or b is zero, percent_tolerance does an exact match, so compare to a small, constant tolerance instead.
- if (a == 0.0f || b == 0.0f)
- {
- return std::abs(a - b) <= g_FloatCloseToZeroTolerance;
- }
-
- if (std::isinf(a) && a == b)
- {
- return true;
- }
-
- if (std::isnan(a) && std::isnan(b))
- {
- return true;
- }
-
- // For unquantized floats we use a tolerance of 1%.
- return armnnUtils::within_percentage_tolerance(a, b);
- }
-};
-
-template<typename T>
-bool SelectiveCompare(T a, T b)
-{
- return SelectiveComparer<T, armnn::IsQuantizedType<T>()>::Compare(a, b);
-};
-
-template<typename T>
-bool SelectiveCompareBoolean(T a, T b)
-{
- return (((a == 0) && (b == 0)) || ((a != 0) && (b != 0)));
-};
-
-template <typename T>
-armnn::PredicateResult CompareTensors(const std::vector<T>& actualData,
- const std::vector<T>& expectedData,
- const armnn::TensorShape& actualShape,
- const armnn::TensorShape& expectedShape,
- bool compareBoolean = false,
- bool isDynamic = false)
-{
- if (actualData.size() != expectedData.size())
- {
- armnn::PredicateResult res(false);
- res.Message() << "Different data size ["
- << actualData.size()
- << "!="
- << expectedData.size()
- << "]";
- return res;
- }
-
- if (actualShape.GetNumDimensions() != expectedShape.GetNumDimensions())
- {
- armnn::PredicateResult res(false);
- res.Message() << "Different number of dimensions ["
- << actualShape.GetNumDimensions()
- << "!="
- << expectedShape.GetNumDimensions()
- << "]";
- return res;
- }
-
- if (actualShape.GetNumElements() != expectedShape.GetNumElements())
- {
- armnn::PredicateResult res(false);
- res.Message() << "Different number of elements ["
- << actualShape.GetNumElements()
- << "!="
- << expectedShape.GetNumElements()
- << "]";
- return res;
- }
-
- unsigned int numberOfDimensions = actualShape.GetNumDimensions();
-
- if (!isDynamic)
- {
- // Checks they are same shape.
- for (unsigned int i = 0; i < numberOfDimensions; ++i)
- {
- if (actualShape[i] != expectedShape[i])
- {
- armnn::PredicateResult res(false);
- res.Message() << "Different shapes ["
- << actualShape[i]
- << "!="
- << expectedShape[i]
- << "]";
- return res;
- }
- }
- }
-
- // Fun iteration over n dimensions.
- std::vector<unsigned int> indices;
- for (unsigned int i = 0; i < numberOfDimensions; i++)
- {
- indices.emplace_back(0);
- }
-
- std::stringstream errorString;
- int numFailedElements = 0;
- constexpr int maxReportedDifferences = 3;
- unsigned int index = 0;
-
- // Compare data element by element.
- while (true)
- {
- bool comparison;
- // As true for uint8_t is non-zero (1-255) we must have a dedicated compare for Booleans.
- if(compareBoolean)
- {
- comparison = SelectiveCompareBoolean(actualData[index], expectedData[index]);
- }
- else
- {
- comparison = SelectiveCompare(actualData[index], expectedData[index]);
- }
-
- if (!comparison)
- {
- ++numFailedElements;
-
- if (numFailedElements <= maxReportedDifferences)
- {
- if (numFailedElements >= 2)
- {
- errorString << ", ";
- }
- errorString << "[";
- for (unsigned int i = 0; i < numberOfDimensions; ++i)
- {
- errorString << indices[i];
- if (i != numberOfDimensions - 1)
- {
- errorString << ",";
- }
- }
- errorString << "]";
-
- errorString << " (" << +actualData[index] << " != " << +expectedData[index] << ")";
- }
- }
-
- ++indices[numberOfDimensions - 1];
- for (unsigned int i=numberOfDimensions-1; i>0; i--)
- {
- if (indices[i] == actualShape[i])
- {
- indices[i] = 0;
- ++indices[i - 1];
- }
- }
- if (indices[0] == actualShape[0])
- {
- break;
- }
-
- index++;
- }
-
- armnn::PredicateResult comparisonResult(true);
- if (numFailedElements > 0)
- {
- comparisonResult.SetResult(false);
- comparisonResult.Message() << numFailedElements << " different values at: ";
- if (numFailedElements > maxReportedDifferences)
- {
- errorString << ", ... (and " << (numFailedElements - maxReportedDifferences) << " other differences)";
- }
- comparisonResult.Message() << errorString.str();
- }
-
- return comparisonResult;
-}
-
-template <typename T>
-std::vector<T> MakeRandomTensor(const armnn::TensorInfo& tensorInfo,
- unsigned int seed,
- float min = -10.0f,
- float max = 10.0f)
-{
- std::mt19937 gen(seed);
- std::uniform_real_distribution<float> dist(min, max);
-
- std::vector<float> init(tensorInfo.GetNumElements());
- for (unsigned int i = 0; i < init.size(); i++)
- {
- init[i] = dist(gen);
- }
-
- const float qScale = tensorInfo.GetQuantizationScale();
- const int32_t qOffset = tensorInfo.GetQuantizationOffset();
-
- return armnnUtils::QuantizedVector<T>(init, qScale, qOffset);
-}
+// This file is deprecated and will be removed soon.
+// Please use the new header in armnnTestUtils instead.
+// This will use the new armnnTestUtils header.
+#include "../../armnnTestUtils/TensorHelpers.hpp"
\ No newline at end of file
diff --git a/src/armnn/test/TestUtils.hpp b/src/armnn/test/TestUtils.hpp
index fa9156b..fe5331e 100644
--- a/src/armnn/test/TestUtils.hpp
+++ b/src/armnn/test/TestUtils.hpp
@@ -1,58 +1,9 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
+#include "../../armnnTestUtils/TestUtils.hpp"
-#include <armnn/INetwork.hpp>
-#include <Graph.hpp>
-#include <Runtime.hpp>
-
-void Connect(armnn::IConnectableLayer* from, armnn::IConnectableLayer* to, const armnn::TensorInfo& tensorInfo,
- unsigned int fromIndex = 0, unsigned int toIndex = 0);
-
-template <typename LayerT>
-bool IsLayerOfType(const armnn::Layer* const layer)
-{
- return (layer->GetType() == armnn::LayerEnumOf<LayerT>());
-}
-
-inline bool CheckSequence(const armnn::Graph::ConstIterator first, const armnn::Graph::ConstIterator last)
-{
- return (first == last);
-}
-
-/// Checks each unary function in Us evaluates true for each correspondent layer in the sequence [first, last).
-template <typename U, typename... Us>
-bool CheckSequence(const armnn::Graph::ConstIterator first, const armnn::Graph::ConstIterator last, U&& u, Us&&... us)
-{
- return u(*first) && CheckSequence(std::next(first), last, us...);
-}
-
-template <typename LayerT>
-bool CheckRelatedLayers(armnn::Graph& graph, const std::list<std::string>& testRelatedLayers)
-{
- for (auto& layer : graph)
- {
- if (layer->GetType() == armnn::LayerEnumOf<LayerT>())
- {
- auto& relatedLayers = layer->GetRelatedLayerNames();
- if (!std::equal(relatedLayers.begin(), relatedLayers.end(), testRelatedLayers.begin(),
- testRelatedLayers.end()))
- {
- return false;
- }
- }
- }
-
- return true;
-}
-
-namespace armnn
-{
-Graph& GetGraphForTesting(IOptimizedNetwork* optNetPtr);
-ModelOptions& GetModelOptionsForTesting(IOptimizedNetwork* optNetPtr);
-profiling::ProfilingService& GetProfilingService(RuntimeImpl* runtime);
-
-} // namespace armnn
\ No newline at end of file
+#pragma message("src/armnn/test/TestUtils.hpp has been deprecated, it is due for removal in 22.08 release." \
+ " Please use from armnnTestUtils library, /src/armnnTestUtils/TestUtils.hpp)
\ No newline at end of file
diff --git a/src/armnn/test/UnitTests.hpp b/src/armnn/test/UnitTests.hpp
index e4a8b96..129a766 100644
--- a/src/armnn/test/UnitTests.hpp
+++ b/src/armnn/test/UnitTests.hpp
@@ -2,187 +2,8 @@
// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
-#include <armnn/Logging.hpp>
-#include <armnn/Utils.hpp>
-#include <reference/RefWorkloadFactory.hpp>
-#include <reference/test/RefWorkloadFactoryHelper.hpp>
+#include "../../armnnTestUtils/UnitTests.hpp"
-#include <backendsCommon/test/LayerTests.hpp>
-#include <backendsCommon/test/WorkloadFactoryHelper.hpp>
-
-#include "TensorHelpers.hpp"
-
-#include <doctest/doctest.h>
-
-inline void ConfigureLoggingTest()
-{
- // Configures logging for both the ARMNN library and this test program.
- armnn::ConfigureLogging(true, true, armnn::LogSeverity::Fatal);
-}
-
-// The following macros require the caller to have defined FactoryType, with one of the following using statements:
-//
-// using FactoryType = armnn::RefWorkloadFactory;
-// using FactoryType = armnn::ClWorkloadFactory;
-// using FactoryType = armnn::NeonWorkloadFactory;
-
-/// Executes CHECK_MESSAGE on CompareTensors() return value so that the predicate_result message is reported.
-/// If the test reports itself as not supported then the tensors are not compared.
-/// Additionally this checks that the supportedness reported by the test matches the name of the test.
-/// Unsupported tests must be 'tagged' by including "UNSUPPORTED" in their name.
-/// This is useful because it clarifies that the feature being tested is not actually supported
-/// (a passed test with the name of a feature would imply that feature was supported).
-/// If support is added for a feature, the test case will fail because the name incorrectly contains UNSUPPORTED.
-/// If support is removed for a feature, the test case will fail because the name doesn't contain UNSUPPORTED.
-template <typename T, std::size_t n>
-void CompareTestResultIfSupported(const std::string& testName, const LayerTestResult<T, n>& testResult)
-{
- bool testNameIndicatesUnsupported = testName.find("UNSUPPORTED") != std::string::npos;
- CHECK_MESSAGE(testNameIndicatesUnsupported != testResult.m_Supported,
- "The test name does not match the supportedness it is reporting");
- if (testResult.m_Supported)
- {
- auto result = CompareTensors(testResult.m_ActualData,
- testResult.m_ExpectedData,
- testResult.m_ActualShape,
- testResult.m_ExpectedShape,
- testResult.m_CompareBoolean);
- CHECK_MESSAGE(result.m_Result, result.m_Message.str());
- }
-}
-
-template <typename T, std::size_t n>
-void CompareTestResultIfSupported(const std::string& testName, const std::vector<LayerTestResult<T, n>>& testResult)
-{
- bool testNameIndicatesUnsupported = testName.find("UNSUPPORTED") != std::string::npos;
- for (unsigned int i = 0; i < testResult.size(); ++i)
- {
- CHECK_MESSAGE(testNameIndicatesUnsupported != testResult[i].m_Supported,
- "The test name does not match the supportedness it is reporting");
- if (testResult[i].m_Supported)
- {
- auto result = CompareTensors(testResult[i].m_ActualData,
- testResult[i].m_ExpectedData,
- testResult[i].m_ActualShape,
- testResult[i].m_ExpectedShape);
- CHECK_MESSAGE(result.m_Result, result.m_Message.str());
- }
- }
-}
-
-template<typename FactoryType, typename TFuncPtr, typename... Args>
-void RunTestFunction(const char* testName, TFuncPtr testFunction, Args... args)
-{
- std::unique_ptr<armnn::IProfiler> profiler = std::make_unique<armnn::IProfiler>();
- armnn::ProfilerManager::GetInstance().RegisterProfiler(profiler.get());
-
- auto memoryManager = WorkloadFactoryHelper<FactoryType>::GetMemoryManager();
- FactoryType workloadFactory = WorkloadFactoryHelper<FactoryType>::GetFactory(memoryManager);
-
- auto testResult = (*testFunction)(workloadFactory, memoryManager, args...);
- CompareTestResultIfSupported(testName, testResult);
-
- armnn::ProfilerManager::GetInstance().RegisterProfiler(nullptr);
-}
-
-
-template<typename FactoryType, typename TFuncPtr, typename... Args>
-void RunTestFunctionUsingTensorHandleFactory(const char* testName, TFuncPtr testFunction, Args... args)
-{
- std::unique_ptr<armnn::IProfiler> profiler = std::make_unique<armnn::IProfiler>();
- armnn::ProfilerManager::GetInstance().RegisterProfiler(profiler.get());
-
- auto memoryManager = WorkloadFactoryHelper<FactoryType>::GetMemoryManager();
- FactoryType workloadFactory = WorkloadFactoryHelper<FactoryType>::GetFactory(memoryManager);
-
- auto tensorHandleFactory = WorkloadFactoryHelper<FactoryType>::GetTensorHandleFactory(memoryManager);
-
- auto testResult = (*testFunction)(workloadFactory, memoryManager, tensorHandleFactory, args...);
- CompareTestResultIfSupported(testName, testResult);
-
- armnn::ProfilerManager::GetInstance().RegisterProfiler(nullptr);
-}
-
-#define ARMNN_SIMPLE_TEST_CASE(TestName, TestFunction) \
- TEST_CASE(#TestName) \
- { \
- TestFunction(); \
- }
-
-#define ARMNN_AUTO_TEST_CASE(TestName, TestFunction, ...) \
- TEST_CASE(#TestName) \
- { \
- RunTestFunction<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
- }
-
-#define ARMNN_AUTO_TEST_FIXTURE(TestName, Fixture, TestFunction, ...) \
- TEST_CASE_FIXTURE(Fixture, #TestName) \
- { \
- RunTestFunction<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
- }
-
-#define ARMNN_AUTO_TEST_CASE_WITH_THF(TestName, TestFunction, ...) \
- TEST_CASE(#TestName) \
- { \
- RunTestFunctionUsingTensorHandleFactory<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
- }
-
-#define ARMNN_AUTO_TEST_FIXTURE_WITH_THF(TestName, Fixture, TestFunction, ...) \
- TEST_CASE_FIXTURE(Fixture, #TestName) \
- { \
- RunTestFunctionUsingTensorHandleFactory<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
- }
-
-template<typename FactoryType, typename TFuncPtr, typename... Args>
-void CompareRefTestFunction(const char* testName, TFuncPtr testFunction, Args... args)
-{
- auto memoryManager = WorkloadFactoryHelper<FactoryType>::GetMemoryManager();
- FactoryType workloadFactory = WorkloadFactoryHelper<FactoryType>::GetFactory(memoryManager);
-
- armnn::RefWorkloadFactory refWorkloadFactory;
-
- auto testResult = (*testFunction)(workloadFactory, memoryManager, refWorkloadFactory, args...);
- CompareTestResultIfSupported(testName, testResult);
-}
-
-template<typename FactoryType, typename TFuncPtr, typename... Args>
-void CompareRefTestFunctionUsingTensorHandleFactory(const char* testName, TFuncPtr testFunction, Args... args)
-{
- auto memoryManager = WorkloadFactoryHelper<FactoryType>::GetMemoryManager();
- FactoryType workloadFactory = WorkloadFactoryHelper<FactoryType>::GetFactory(memoryManager);
-
- armnn::RefWorkloadFactory refWorkloadFactory;
- auto tensorHandleFactory = WorkloadFactoryHelper<FactoryType>::GetTensorHandleFactory(memoryManager);
- auto refTensorHandleFactory =
- RefWorkloadFactoryHelper::GetTensorHandleFactory(memoryManager);
-
- auto testResult = (*testFunction)(
- workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, args...);
- CompareTestResultIfSupported(testName, testResult);
-}
-
-#define ARMNN_COMPARE_REF_AUTO_TEST_CASE(TestName, TestFunction, ...) \
- TEST_CASE(#TestName) \
- { \
- CompareRefTestFunction<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
- }
-
-#define ARMNN_COMPARE_REF_AUTO_TEST_CASE_WITH_THF(TestName, TestFunction, ...) \
- TEST_CASE(#TestName) \
- { \
- CompareRefTestFunctionUsingTensorHandleFactory<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
- }
-
-#define ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(TestName, Fixture, TestFunction, ...) \
- TEST_CASE_FIXTURE(Fixture, #TestName) \
- { \
- CompareRefTestFunction<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
- }
-
-#define ARMNN_COMPARE_REF_FIXTURE_TEST_CASE_WITH_THF(TestName, Fixture, TestFunction, ...) \
- TEST_CASE_FIXTURE(Fixture, #TestName) \
- { \
- CompareRefTestFunctionUsingTensorHandleFactory<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
- }
+#pragma message("src/armnn/test/UnitTests.hpp has been deprecated, it is due for removal in 22.08 release." \
+ " Please use from armnnTestUtils library, /src/armnnTestUtils/UnitTests.hpp)
\ No newline at end of file
diff --git a/src/armnn/test/optimizations/AddBroadcastReshapeLayerTests.cpp b/src/armnn/test/optimizations/AddBroadcastReshapeLayerTests.cpp
index 7573005..0636a00 100644
--- a/src/armnn/test/optimizations/AddBroadcastReshapeLayerTests.cpp
+++ b/src/armnn/test/optimizations/AddBroadcastReshapeLayerTests.cpp
@@ -3,8 +3,8 @@
// SPDX-License-Identifier: MIT
//
-#include "../GraphUtils.hpp"
-#include "../TestUtils.hpp"
+#include <GraphUtils.hpp>
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp b/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp
index 7b326fa..4aacf7f 100644
--- a/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp
+++ b/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <BFloat16.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp b/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp
index f74ab0f..531a0dd 100644
--- a/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp
+++ b/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
#include <Half.hpp>
diff --git a/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp b/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp
index c455152..4c453cc 100644
--- a/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp
+++ b/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/FoldPadTests.cpp b/src/armnn/test/optimizations/FoldPadTests.cpp
index a598983..a64660f 100644
--- a/src/armnn/test/optimizations/FoldPadTests.cpp
+++ b/src/armnn/test/optimizations/FoldPadTests.cpp
@@ -5,7 +5,7 @@
#include "LayersFwd.hpp"
#include <Network.hpp>
-#include <test/TestUtils.hpp>
+#include <TestUtils.hpp>
#include <doctest/doctest.h>
#include <backendsCommon/TensorHandle.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp b/src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp
index 63cd170..37d7701 100644
--- a/src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp
+++ b/src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/Fp32NetworkToFp16ConverterTests.cpp b/src/armnn/test/optimizations/Fp32NetworkToFp16ConverterTests.cpp
index e2ac1bd..bc88399 100644
--- a/src/armnn/test/optimizations/Fp32NetworkToFp16ConverterTests.cpp
+++ b/src/armnn/test/optimizations/Fp32NetworkToFp16ConverterTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/FuseActivationTests.cpp b/src/armnn/test/optimizations/FuseActivationTests.cpp
index 54a9d9a..99b2b80 100644
--- a/src/armnn/test/optimizations/FuseActivationTests.cpp
+++ b/src/armnn/test/optimizations/FuseActivationTests.cpp
@@ -8,8 +8,8 @@
#include <Network.hpp>
#include <ResolveType.hpp>
#include <armnn/INetwork.hpp>
-#include "test/GraphUtils.hpp"
-#include <test/TestUtils.hpp>
+#include <GraphUtils.hpp>
+#include <TestUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/armnn/test/optimizations/FuseBatchNormTests.cpp b/src/armnn/test/optimizations/FuseBatchNormTests.cpp
index 0e969c1..70cffea 100644
--- a/src/armnn/test/optimizations/FuseBatchNormTests.cpp
+++ b/src/armnn/test/optimizations/FuseBatchNormTests.cpp
@@ -8,7 +8,7 @@
#include <Network.hpp>
#include <ResolveType.hpp>
#include <armnn/INetwork.hpp>
-#include <test/TestUtils.hpp>
+#include <TestUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/armnn/test/optimizations/InsertDebugLayerTests.cpp b/src/armnn/test/optimizations/InsertDebugLayerTests.cpp
index 03d0d22..523ffcf 100644
--- a/src/armnn/test/optimizations/InsertDebugLayerTests.cpp
+++ b/src/armnn/test/optimizations/InsertDebugLayerTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/MovePermuteUpTests.cpp b/src/armnn/test/optimizations/MovePermuteUpTests.cpp
index 38a65a6..152e799 100644
--- a/src/armnn/test/optimizations/MovePermuteUpTests.cpp
+++ b/src/armnn/test/optimizations/MovePermuteUpTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/MoveTransposeUpTests.cpp b/src/armnn/test/optimizations/MoveTransposeUpTests.cpp
index 68d277a..09bf9ae 100644
--- a/src/armnn/test/optimizations/MoveTransposeUpTests.cpp
+++ b/src/armnn/test/optimizations/MoveTransposeUpTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/OptimizeConsecutiveReshapesTests.cpp b/src/armnn/test/optimizations/OptimizeConsecutiveReshapesTests.cpp
index 694b103..599b44a 100644
--- a/src/armnn/test/optimizations/OptimizeConsecutiveReshapesTests.cpp
+++ b/src/armnn/test/optimizations/OptimizeConsecutiveReshapesTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/OptimizeInverseConversionsTests.cpp b/src/armnn/test/optimizations/OptimizeInverseConversionsTests.cpp
index 4b6dfe5..1e03140 100644
--- a/src/armnn/test/optimizations/OptimizeInverseConversionsTests.cpp
+++ b/src/armnn/test/optimizations/OptimizeInverseConversionsTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/OptimizeInversePermutesTests.cpp b/src/armnn/test/optimizations/OptimizeInversePermutesTests.cpp
index 98c84d4..cfd1a23 100644
--- a/src/armnn/test/optimizations/OptimizeInversePermutesTests.cpp
+++ b/src/armnn/test/optimizations/OptimizeInversePermutesTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/PermuteAndBatchToSpaceAsDepthToSpaceTests.cpp b/src/armnn/test/optimizations/PermuteAndBatchToSpaceAsDepthToSpaceTests.cpp
index f862315..d87d3f0 100644
--- a/src/armnn/test/optimizations/PermuteAndBatchToSpaceAsDepthToSpaceTests.cpp
+++ b/src/armnn/test/optimizations/PermuteAndBatchToSpaceAsDepthToSpaceTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Network.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/PermuteAsReshapeTests.cpp b/src/armnn/test/optimizations/PermuteAsReshapeTests.cpp
index fdd0a6d..b143078 100644
--- a/src/armnn/test/optimizations/PermuteAsReshapeTests.cpp
+++ b/src/armnn/test/optimizations/PermuteAsReshapeTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/RedirectMembersToConstantInputsTests.cpp b/src/armnn/test/optimizations/RedirectMembersToConstantInputsTests.cpp
index 46b06a5..b3f9ed8 100644
--- a/src/armnn/test/optimizations/RedirectMembersToConstantInputsTests.cpp
+++ b/src/armnn/test/optimizations/RedirectMembersToConstantInputsTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/ReduceMultipleAxesTests.cpp b/src/armnn/test/optimizations/ReduceMultipleAxesTests.cpp
index 692f371..cf1dfa0 100644
--- a/src/armnn/test/optimizations/ReduceMultipleAxesTests.cpp
+++ b/src/armnn/test/optimizations/ReduceMultipleAxesTests.cpp
@@ -3,8 +3,8 @@
// SPDX-License-Identifier: MIT
//
-#include "../GraphUtils.hpp"
-#include "../TestUtils.hpp"
+#include <GraphUtils.hpp>
+#include <TestUtils.hpp>
#include <armnn/INetwork.hpp>
diff --git a/src/armnn/test/optimizations/SquashEqualSiblingsTests.cpp b/src/armnn/test/optimizations/SquashEqualSiblingsTests.cpp
index 069d284..e66bb75 100644
--- a/src/armnn/test/optimizations/SquashEqualSiblingsTests.cpp
+++ b/src/armnn/test/optimizations/SquashEqualSiblingsTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnn/test/optimizations/TransposeAsReshapeTests.cpp b/src/armnn/test/optimizations/TransposeAsReshapeTests.cpp
index 5d1d950..371f3ac 100644
--- a/src/armnn/test/optimizations/TransposeAsReshapeTests.cpp
+++ b/src/armnn/test/optimizations/TransposeAsReshapeTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "../TestUtils.hpp"
+#include <TestUtils.hpp>
#include <Optimizer.hpp>
diff --git a/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp b/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp
index f460059..21809eb 100644
--- a/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp
+++ b/src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp
@@ -6,7 +6,7 @@
#pragma once
#include "SchemaSerialize.hpp"
-#include "test/TensorHelpers.hpp"
+#include "TensorHelpers.hpp"
#include "flatbuffers/idl.h"
#include "flatbuffers/util.h"
diff --git a/src/armnnTestUtils/CMakeLists.txt b/src/armnnTestUtils/CMakeLists.txt
new file mode 100755
index 0000000..3738fad
--- /dev/null
+++ b/src/armnnTestUtils/CMakeLists.txt
@@ -0,0 +1,50 @@
+#
+# Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+# SPDX-License-Identifier: MIT
+#
+
+# armnnTestUtils library provides useful test functions for backend developers.
+set(armnnTestUtils_sources)
+list(APPEND armnnTestUtils_sources
+ ../../include/armnnTestUtils/DataLayoutUtils.hpp
+ ../../include/armnnTestUtils/LayerTestResult.hpp
+ ../../include/armnnTestUtils/PredicateResult.hpp
+ ../../include/armnnTestUtils/TensorCopyUtils.hpp
+ TensorHelpers.hpp
+ CreateWorkload.hpp
+ CommonTestUtils.cpp
+ CommonTestUtils.hpp
+ DataTypeUtils.hpp
+ GraphUtils.cpp
+ GraphUtils.hpp
+ TensorCopyUtils.cpp
+ TestUtils.cpp
+ TestUtils.hpp
+ UnitTests.cpp
+ UnitTests.hpp
+ WorkloadTestUtils.hpp
+ )
+
+add_library_ex(armnnTestUtils SHARED ${armnnTestUtils_sources})
+
+set_target_properties(armnnTestUtils PROPERTIES LIBRARY_OUTPUT_DIRECTORY ${PROJECT_BINARY_DIR})
+
+target_include_directories(armnnTestUtils
+ PUBLIC
+ $<INSTALL_INTERFACE:include>
+ $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/include>
+ PRIVATE
+ ${CMAKE_CURRENT_SOURCE_DIR}/src)
+
+target_include_directories(armnnTestUtils PRIVATE ../armnn)
+target_include_directories(armnnTestUtils PRIVATE ../armnnUtils)
+target_include_directories(armnnTestUtils PRIVATE ../backends)
+target_include_directories(armnnTestUtils PRIVATE ../profiling)
+
+install(TARGETS armnnTestUtils
+ EXPORT armnn-targets
+ LIBRARY DESTINATION ${CMAKE_INSTALL_LIBDIR}
+ ARCHIVE DESTINATION ${CMAKE_INSTALL_LIBDIR}
+ RUNTIME DESTINATION ${CMAKE_INSTALL_BINDIR})
+
+add_library(Armnn::armnnTestUtils ALIAS armnnTestUtils)
\ No newline at end of file
diff --git a/src/backends/backendsCommon/test/CommonTestUtils.cpp b/src/armnnTestUtils/CommonTestUtils.cpp
similarity index 96%
rename from src/backends/backendsCommon/test/CommonTestUtils.cpp
rename to src/armnnTestUtils/CommonTestUtils.cpp
index 287c71e..c853305 100644
--- a/src/backends/backendsCommon/test/CommonTestUtils.cpp
+++ b/src/armnnTestUtils/CommonTestUtils.cpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
diff --git a/src/armnnTestUtils/CommonTestUtils.hpp b/src/armnnTestUtils/CommonTestUtils.hpp
new file mode 100644
index 0000000..a4babc5
--- /dev/null
+++ b/src/armnnTestUtils/CommonTestUtils.hpp
@@ -0,0 +1,119 @@
+//
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "TestUtils.hpp"
+
+#include <Graph.hpp>
+#include <SubgraphView.hpp>
+#include <SubgraphViewSelector.hpp>
+#include <ResolveType.hpp>
+
+#include <armnn/BackendRegistry.hpp>
+
+#include <armnn/Types.hpp>
+#include <backendsCommon/TensorHandle.hpp>
+
+#include <algorithm>
+#include <random>
+#include <vector>
+
+// Checks that two collections have the exact same contents (in any order)
+// The given collections do not have to contain duplicates
+// Cannot use std::sort here because std lists have their own std::list::sort method
+template <typename CollectionType>
+bool AreEqual(const CollectionType& lhs, const CollectionType& rhs)
+{
+ if (lhs.size() != rhs.size())
+ {
+ return false;
+ }
+
+ auto lhs_it = std::find_if(lhs.begin(), lhs.end(), [&rhs](auto& item)
+ {
+ return std::find(rhs.begin(), rhs.end(), item) == rhs.end();
+ });
+
+ return lhs_it == lhs.end();
+}
+
+// Checks that the given collection contains the specified item
+template <typename CollectionType>
+bool Contains(const CollectionType& collection, const typename CollectionType::value_type& item)
+{
+ return std::find(collection.begin(), collection.end(), item) != collection.end();
+}
+
+// Checks that the given map contains the specified key
+template <typename MapType>
+bool Contains(const MapType& map, const typename MapType::key_type& key)
+{
+ return map.find(key) != map.end();
+}
+
+// Utility template for comparing tensor elements
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+inline bool Compare(T a, T b, float tolerance = 0.000001f)
+{
+ if (ArmnnType == armnn::DataType::Boolean)
+ {
+ // NOTE: Boolean is represented as uint8_t (with zero equals
+ // false and everything else equals true), therefore values
+ // need to be casted to bool before comparing them
+ return static_cast<bool>(a) == static_cast<bool>(b);
+ }
+
+ // NOTE: All other types can be cast to float and compared with
+ // a certain level of tolerance
+ return std::fabs(static_cast<float>(a) - static_cast<float>(b)) <= tolerance;
+}
+
+template <typename ConvolutionLayer>
+void SetWeightAndBias(ConvolutionLayer* layer, const armnn::TensorInfo& weightInfo, const armnn::TensorInfo& biasInfo)
+{
+ layer->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weightInfo);
+ layer->m_Bias = std::make_unique<armnn::ScopedTensorHandle>(biasInfo);
+
+ layer->m_Weight->Allocate();
+ layer->m_Bias->Allocate();
+}
+
+armnn::SubgraphView::InputSlots CreateInputsFrom(const std::vector<armnn::Layer*>& layers);
+
+armnn::SubgraphView::OutputSlots CreateOutputsFrom(const std::vector<armnn::Layer*>& layers);
+
+armnn::SubgraphView::SubgraphViewPtr CreateSubgraphViewFrom(armnn::SubgraphView::InputSlots&& inputs,
+ armnn::SubgraphView::OutputSlots&& outputs,
+ armnn::SubgraphView::Layers&& layers);
+
+armnn::IBackendInternalUniquePtr CreateBackendObject(const armnn::BackendId& backendId);
+
+armnn::TensorShape MakeTensorShape(unsigned int batches,
+ unsigned int channels,
+ unsigned int height,
+ unsigned int width,
+ armnn::DataLayout layout);
+
+template<typename DataType>
+static std::vector<DataType> GenerateRandomData(size_t size)
+{
+ constexpr bool isIntegerType = std::is_integral<DataType>::value;
+ using Distribution =
+ typename std::conditional<isIntegerType,
+ std::uniform_int_distribution<DataType>,
+ std::uniform_real_distribution<DataType>>::type;
+
+ static constexpr DataType lowerLimit = std::numeric_limits<DataType>::min();
+ static constexpr DataType upperLimit = std::numeric_limits<DataType>::max();
+
+ static Distribution distribution(lowerLimit, upperLimit);
+ static std::default_random_engine generator;
+
+ std::vector<DataType> randomData(size);
+ generate(randomData.begin(), randomData.end(), []() { return distribution(generator); });
+
+ return randomData;
+}
diff --git a/src/armnnTestUtils/CreateWorkload.hpp b/src/armnnTestUtils/CreateWorkload.hpp
new file mode 100644
index 0000000..ea8a436
--- /dev/null
+++ b/src/armnnTestUtils/CreateWorkload.hpp
@@ -0,0 +1,2316 @@
+//
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "TestUtils.hpp"
+
+#include <Graph.hpp>
+#include <Network.hpp>
+#include <ResolveType.hpp>
+
+#include <armnnUtils/DataLayoutIndexed.hpp>
+#include <armnn/utility/Assert.hpp>
+#include <armnn/utility/IgnoreUnused.hpp>
+#include <armnn/utility/PolymorphicDowncast.hpp>
+
+#include <backendsCommon/TensorHandle.hpp>
+#include <backendsCommon/WorkloadData.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+#include <doctest/doctest.h>
+
+#include <utility>
+
+using namespace armnn;
+
+namespace
+{
+
+using namespace std;
+
+// Calls CreateWorkload for a layer, and checks the returned pointer is of the correct type.
+template<typename Workload>
+std::unique_ptr<Workload> MakeAndCheckWorkload(Layer& layer,
+ const IWorkloadFactory& factory,
+ const ModelOptions& modelOptions = {})
+{
+ std::unique_ptr<IWorkload> workload = layer.CreateWorkload(factory);
+ CHECK_MESSAGE(workload.get() == PolymorphicDowncast<Workload*>(workload.get()),
+ "Cannot convert to derived class");
+ std::string reasonIfUnsupported;
+ layer.SetBackendId(factory.GetBackendId());
+ CHECK(factory.IsLayerSupported(layer, layer.GetDataType(), reasonIfUnsupported, modelOptions));
+ return std::unique_ptr<Workload>(static_cast<Workload*>(workload.release()));
+}
+
+// Helper function to create tensor handlers for workloads, assuming they all use the same factory.
+void CreateTensorHandles(armnn::Graph& graph,
+ armnn::IWorkloadFactory& factory)
+{
+ TensorHandleFactoryRegistry tmpRegistry;
+ for (auto&& layer : graph.TopologicalSort())
+ {
+ layer->CreateTensorHandles(tmpRegistry, factory);
+ }
+}
+
+/////////////////////////////////////////////////////////////////////////////////////////////
+// The following functions are called by backendsCommon/test/CreateWorkload*.cpp
+// They build very simple graphs, and then create a workload.
+// Some checks are performed on the workload to ensure parameters have been passed correctly.
+// They return the created workloads so that backend-specific checks can be performed.
+/////////////////////////////////////////////////////////////////////////////////////////////
+
+template <typename ActivationWorkload, armnn::DataType DataType>
+std::unique_ptr<ActivationWorkload> CreateActivationWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ // Creates the layer we're testing.
+ ActivationDescriptor layerDesc;
+ layerDesc.m_Function = ActivationFunction::Abs;
+ layerDesc.m_A = 3.5f;
+ layerDesc.m_B = -10.0f;
+
+ ActivationLayer* const layer = graph.AddLayer<ActivationLayer>(layerDesc, "layer");
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo tensorInfo({1, 1}, DataType);
+
+ Connect(input, layer, tensorInfo);
+ Connect(layer, output, tensorInfo);
+
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<ActivationWorkload>(*layer, factory);
+
+ ActivationQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+ CHECK(queueDescriptor.m_Parameters.m_A == 3.5f);
+ CHECK(queueDescriptor.m_Parameters.m_B == -10.0f);
+ CHECK((queueDescriptor.m_Parameters.m_Function == ActivationFunction::Abs));
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename WorkloadType,
+ typename DescriptorType,
+ typename LayerType,
+ armnn::DataType DataType>
+std::unique_ptr<WorkloadType> CreateElementwiseWorkloadTest(armnn::IWorkloadFactory & factory,
+ armnn::Graph & graph)
+{
+ // Creates the layer we're testing.
+ Layer* const layer = graph.AddLayer<LayerType>("layer");
+
+ // Creates extra layers.
+ Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");
+ Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo tensorInfo({2, 3}, DataType);
+ Connect(input1, layer, tensorInfo, 0, 0);
+ Connect(input2, layer, tensorInfo, 0, 1);
+ Connect(layer, output, tensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);
+
+ DescriptorType queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 2);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template<typename WorkloadType,
+ typename DescriptorType,
+ armnn::DataType DataType>
+std::unique_ptr<WorkloadType> CreateSubtractionWithBlobWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ // Creates the layer we're testing.
+ SubtractionLayer* const layer = graph.AddLayer<SubtractionLayer>("layer");
+
+ auto activationDesc = std::make_shared<ActivationDescriptor>();
+ activationDesc->m_A = 10.0f;
+ activationDesc->m_B = 5.0f;
+ activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
+
+ layer->SetAdditionalInfoForObject(activationDesc);
+
+ // Creates extra layers.
+ Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");
+ Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo tensorInfo({2, 3}, DataType);
+ Connect(input1, layer, tensorInfo, 0, 0);
+ Connect(input2, layer, tensorInfo, 0, 1);
+ Connect(layer, output, tensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Check that the additional information can be queried from the layer
+ std::shared_ptr<ActivationDescriptor>
+ activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();
+
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(
+ static_cast<ActivationFunction>(activationDescPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
+ );
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);
+
+ DescriptorType queueDescriptor = workload->GetData();
+
+ const ActivationDescriptor* queueDescBlobPtr =
+ queueDescriptor.template GetAdditionalInformation<ActivationDescriptor>();
+ IgnoreUnused(queueDescBlobPtr);
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(
+ static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
+ );
+
+ CHECK(queueDescriptor.m_Inputs.size() == 2);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ return workload;
+}
+
+template<typename WorkloadType,
+ typename DescriptorType,
+ armnn::DataType DataType>
+std::unique_ptr<WorkloadType> CreateMultiplicationWithBlobWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ // Creates the layer we're testing.
+ MultiplicationLayer* const layer = graph.AddLayer<MultiplicationLayer>("layer");
+
+ auto activationDesc = std::make_shared<ActivationDescriptor>();
+ activationDesc->m_A = 10.0f;
+ activationDesc->m_B = 5.0f;
+ activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
+
+ layer->SetAdditionalInfoForObject(activationDesc);
+
+ // Creates extra layers.
+ Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");
+ Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo tensorInfo({2, 3}, DataType);
+ Connect(input1, layer, tensorInfo, 0, 0);
+ Connect(input2, layer, tensorInfo, 0, 1);
+ Connect(layer, output, tensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Check that the additional information can be queried from the layer
+ std::shared_ptr<ActivationDescriptor>
+ activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();
+
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(
+ static_cast<ActivationFunction>(activationDescPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
+ );
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);
+
+ DescriptorType queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 2);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+ const ActivationDescriptor* queueDescBlobPtr =
+ queueDescriptor.template GetAdditionalInformation<ActivationDescriptor>();
+ IgnoreUnused(queueDescBlobPtr);
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(
+ static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
+ );
+
+ return workload;// Returns so we can do extra, backend-specific tests.
+}
+
+template<typename WorkloadType,
+ typename DescriptorType,
+ armnn::DataType DataType>
+std::unique_ptr<WorkloadType> CreateAdditionWithBlobWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ // Creates the layer we're testing.
+ AdditionLayer* const layer = graph.AddLayer<AdditionLayer>("layer");
+
+ auto activationDesc = std::make_shared<ActivationDescriptor>();
+ activationDesc->m_A = 10.0f;
+ activationDesc->m_B = 5.0f;
+ activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
+
+ layer->SetAdditionalInfoForObject(activationDesc);
+
+ // Creates extra layers.
+ Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");
+ Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo tensorInfo({2, 3}, DataType);
+ Connect(input1, layer, tensorInfo, 0, 0);
+ Connect(input2, layer, tensorInfo, 0, 1);
+ Connect(layer, output, tensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Check that the additional information can be queried from the layer
+ std::shared_ptr<ActivationDescriptor>
+ activationDescPtr = layer->template GetAdditionalInformation<ActivationDescriptor>();
+
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(
+ static_cast<ActivationFunction>(activationDescPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
+ );
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);
+
+ DescriptorType queueDescriptor = workload->GetData();
+ const ActivationDescriptor* queueDescBlobPtr =
+ queueDescriptor.template GetAdditionalInformation<ActivationDescriptor>();
+ IgnoreUnused(queueDescBlobPtr);
+ CHECK(queueDescriptor.m_Inputs.size() == 2);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(
+ static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
+ );
+
+ return workload;
+}
+
+template <typename WorkloadType,
+ typename DescriptorType,
+ armnn::DataType DataType>
+std::unique_ptr<WorkloadType> CreateElementwiseUnaryWorkloadTest(armnn::IWorkloadFactory & factory,
+ armnn::Graph & graph,
+ armnn::UnaryOperation op)
+{
+ ElementwiseUnaryDescriptor desc = ElementwiseUnaryDescriptor(op);
+ Layer* const layer = graph.AddLayer<armnn::ElementwiseUnaryLayer>(desc, "layer");
+
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ armnn::TensorInfo tensorInfo({ 2, 3 }, DataType);
+ Connect(input, layer, tensorInfo, 0, 0);
+ Connect(layer, output, tensorInfo, 0, 0);
+ CreateTensorHandles(graph, factory);
+
+ auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);
+ DescriptorType queueDescriptor = workload->GetData();
+
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ return workload;
+}
+
+template <typename BatchNormalizationWorkloadType, armnn::DataType DataType>
+std::unique_ptr<BatchNormalizationWorkloadType> CreateBatchNormalizationWorkloadTest(
+ armnn::IWorkloadFactory& factory, armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW)
+{
+ TensorShape tensorShape;
+ switch (dataLayout)
+ {
+ case DataLayout::NHWC:
+ tensorShape = { 2, 4, 4, 3 };
+ break;
+ case DataLayout::NCHW:
+ default:
+ tensorShape = { 2, 3, 4, 4 };
+ }
+
+ // Creates the layer we're testing.
+ BatchNormalizationDescriptor layerDesc;
+ layerDesc.m_Eps = 0.05f;
+ layerDesc.m_DataLayout = dataLayout;
+
+ BatchNormalizationLayer* const layer = graph.AddLayer<BatchNormalizationLayer>(layerDesc, "layer");
+
+ armnn::TensorInfo weightInfo({3}, DataType);
+ layer->m_Mean = std::make_unique<ScopedTensorHandle>(weightInfo);
+ layer->m_Variance = std::make_unique<ScopedTensorHandle>(weightInfo);
+ layer->m_Beta = std::make_unique<ScopedTensorHandle>(weightInfo);
+ layer->m_Gamma = std::make_unique<ScopedTensorHandle>(weightInfo);
+ layer->m_Mean->Allocate();
+ layer->m_Variance->Allocate();
+ layer->m_Beta->Allocate();
+ layer->m_Gamma->Allocate();
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo tensorInfo(tensorShape, DataType);
+ Connect(input, layer, tensorInfo);
+ Connect(layer, output, tensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<BatchNormalizationWorkloadType>(*layer, factory);
+ BatchNormalizationQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Parameters.m_Eps == 0.05f);
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+ CHECK((queueDescriptor.m_Mean->GetTensorInfo() == TensorInfo({3}, DataType)));
+ CHECK((queueDescriptor.m_Variance->GetTensorInfo() == TensorInfo({3}, DataType)));
+ CHECK((queueDescriptor.m_Gamma->GetTensorInfo() == TensorInfo({3}, DataType)));
+ CHECK((queueDescriptor.m_Beta->GetTensorInfo() == TensorInfo({3}, DataType)));
+ CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename BatchNormalizationWorkloadType, armnn::DataType DataType>
+std::unique_ptr<BatchNormalizationWorkloadType> CreateBatchNormalizationWithBlobWorkloadTest(
+ armnn::IWorkloadFactory& factory, armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW)
+{
+ TensorShape tensorShape;
+ switch (dataLayout)
+ {
+ case DataLayout::NHWC:
+ tensorShape = { 2, 4, 4, 3 };
+ break;
+ case DataLayout::NCHW:
+ default:
+ tensorShape = { 2, 3, 4, 4 };
+ }
+
+ // Creates the layer we're testing.
+ BatchNormalizationDescriptor layerDesc;
+ layerDesc.m_Eps = 0.05f;
+ layerDesc.m_DataLayout = dataLayout;
+
+ BatchNormalizationLayer* const layer = graph.AddLayer<BatchNormalizationLayer>(layerDesc, "layer");
+
+ armnn::TensorInfo weightInfo({3}, DataType);
+ layer->m_Mean = std::make_unique<ScopedTensorHandle>(weightInfo);
+ layer->m_Variance = std::make_unique<ScopedTensorHandle>(weightInfo);
+ layer->m_Beta = std::make_unique<ScopedTensorHandle>(weightInfo);
+ layer->m_Gamma = std::make_unique<ScopedTensorHandle>(weightInfo);
+ layer->m_Mean->Allocate();
+ layer->m_Variance->Allocate();
+ layer->m_Beta->Allocate();
+ layer->m_Gamma->Allocate();
+
+ auto activationDesc = std::make_shared<ActivationDescriptor>();
+ activationDesc->m_A = 10.0f;
+ activationDesc->m_B = 5.0f;
+ activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
+
+ layer->SetAdditionalInfoForObject(activationDesc);
+
+ // Check that the additional information can be queried from the layer
+ std::shared_ptr<ActivationDescriptor> activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(
+ static_cast<ActivationFunction>(activationDescPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
+ );
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo tensorInfo(tensorShape, DataType);
+ Connect(input, layer, tensorInfo);
+ Connect(layer, output, tensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<BatchNormalizationWorkloadType>(*layer, factory);
+ BatchNormalizationQueueDescriptor queueDescriptor = workload->GetData();
+ const ActivationDescriptor* queueDescBlobPtr = queueDescriptor.GetAdditionalInformation<ActivationDescriptor>();
+ IgnoreUnused(queueDescBlobPtr);
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(
+ static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
+ );
+
+ CHECK(queueDescriptor.m_Parameters.m_Eps == 0.05f);
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+ CHECK((queueDescriptor.m_Mean->GetTensorInfo() == TensorInfo({3}, DataType)));
+ CHECK((queueDescriptor.m_Variance->GetTensorInfo() == TensorInfo({3}, DataType)));
+ CHECK((queueDescriptor.m_Gamma->GetTensorInfo() == TensorInfo({3}, DataType)));
+ CHECK((queueDescriptor.m_Beta->GetTensorInfo() == TensorInfo({3}, DataType)));
+ CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename Convolution2dWorkload, armnn::DataType DataType>
+std::unique_ptr<Convolution2dWorkload> CreateConvolution2dWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph,
+ DataLayout dataLayout = DataLayout::NCHW,
+ const ModelOptions& modelOptions = {})
+{
+ // Creates 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;
+ layerDesc.m_DataLayout = dataLayout;
+
+ Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");
+
+ TensorShape weightShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 5, 3} : TensorShape{2, 5, 3, 3};
+ TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 8, 16} : TensorShape{2, 8, 16, 3};
+ TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 2, 2, 10} : TensorShape{2, 2, 10, 2};
+
+ layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo(weightShape, DataType));
+ layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({2}, GetBiasDataType(DataType)));
+
+ layer->m_Weight->Allocate();
+ layer->m_Bias->Allocate();
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ Connect(input, layer, TensorInfo(inputShape, DataType));
+ Connect(layer, output, TensorInfo(outputShape, DataType));
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory, modelOptions);
+
+ Convolution2dQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Parameters.m_StrideX == 2);
+ CHECK(queueDescriptor.m_Parameters.m_StrideY == 4);
+ CHECK(queueDescriptor.m_Parameters.m_PadLeft == 3);
+ CHECK(queueDescriptor.m_Parameters.m_PadRight == 3);
+ CHECK(queueDescriptor.m_Parameters.m_PadTop == 1);
+ CHECK(queueDescriptor.m_Parameters.m_PadBottom == 1);
+ CHECK(queueDescriptor.m_Parameters.m_BiasEnabled);
+ CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
+
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+ CHECK((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo(weightShape, DataType)));
+ CHECK((queueDescriptor.m_Bias->GetTensorInfo() ==
+ TensorInfo({2}, GetBiasDataType(DataType))));
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template<typename Convolution2dWorkload, armnn::DataType DataType>
+std::unique_ptr<Convolution2dWorkload> CreateConvolution2dFusedActivationWithBlobWorkloadTest(
+ armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph,
+ DataLayout dataLayout = DataLayout::NCHW,
+ const ModelOptions& modelOptions = {})
+{
+ // Creates 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;
+ layerDesc.m_DataLayout = dataLayout;
+
+
+ Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");
+
+ TensorShape weightShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 5, 3} : TensorShape{2, 5, 3, 3};
+ TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 8, 16} : TensorShape{2, 8, 16, 3};
+ TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 2, 2, 10} : TensorShape{2, 2, 10, 2};
+
+ layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo(weightShape, DataType));
+ layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({2}, GetBiasDataType(DataType)));
+
+ layer->m_Weight->Allocate();
+ layer->m_Bias->Allocate();
+
+ auto activationDesc = std::make_shared<ActivationDescriptor>();
+ activationDesc->m_A = 10.0f;
+ activationDesc->m_B = 5.0f;
+ activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
+
+ layer->SetAdditionalInfoForObject(activationDesc);
+
+ // Check that the additional information can be queried from the layer
+ std::shared_ptr<ActivationDescriptor> activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();
+
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(
+ static_cast<ActivationFunction>(activationDescPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
+ );
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ Connect(input, layer, TensorInfo(inputShape, DataType));
+ Connect(layer, output, TensorInfo(outputShape, DataType));
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory, modelOptions);
+
+ Convolution2dQueueDescriptor queueDescriptor = workload->GetData();
+ const ActivationDescriptor* queueDescBlobPtr = queueDescriptor.GetAdditionalInformation<ActivationDescriptor>();
+ IgnoreUnused(queueDescBlobPtr);
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(
+ static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
+ );
+
+ CHECK(queueDescriptor.m_Parameters.m_StrideX == 2);
+ CHECK(queueDescriptor.m_Parameters.m_StrideY == 4);
+ CHECK(queueDescriptor.m_Parameters.m_PadLeft == 3);
+ CHECK(queueDescriptor.m_Parameters.m_PadRight == 3);
+ CHECK(queueDescriptor.m_Parameters.m_PadTop == 1);
+ CHECK(queueDescriptor.m_Parameters.m_PadBottom == 1);
+ CHECK(queueDescriptor.m_Parameters.m_BiasEnabled);
+ CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+ CHECK((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo(weightShape, DataType)));
+ CHECK((queueDescriptor.m_Bias->GetTensorInfo() ==
+ TensorInfo({2}, GetBiasDataType(DataType))));
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename Convolution2dWorkload, armnn::DataType DataType>
+std::unique_ptr<Convolution2dWorkload> CreateConvolution2dWorkloadFastMathTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph,
+ DataLayout dataLayout = DataLayout::NCHW,
+ const ModelOptions& modelOptions = {})
+{
+ // Creates the layer we're testing.
+ Convolution2dDescriptor layerDesc;
+ layerDesc.m_PadLeft = 0;
+ layerDesc.m_PadRight = 0;
+ layerDesc.m_PadTop = 0;
+ layerDesc.m_PadBottom = 0;
+ layerDesc.m_StrideX = 1;
+ layerDesc.m_StrideY = 1;
+ layerDesc.m_BiasEnabled = false;
+ layerDesc.m_DataLayout = dataLayout;
+
+ Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");
+
+ TensorShape weightShape = TensorShape{32, 32, 3, 3};
+ TensorShape inputShape = TensorShape{1, 32, 149, 149};
+ TensorShape outputShape = TensorShape{1, 32, 147, 147};
+
+ layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo(weightShape, DataType));
+ layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({2}, GetBiasDataType(DataType)));
+
+ layer->m_Weight->Allocate();
+ layer->m_Bias->Allocate();
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ Connect(input, layer, TensorInfo(inputShape, DataType));
+ Connect(layer, output, TensorInfo(outputShape, DataType));
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory, modelOptions);
+
+ Convolution2dQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Parameters.m_StrideX == 1);
+ CHECK(queueDescriptor.m_Parameters.m_StrideY == 1);
+ CHECK(queueDescriptor.m_Parameters.m_PadLeft == 0);
+ CHECK(queueDescriptor.m_Parameters.m_PadRight == 0);
+ CHECK(queueDescriptor.m_Parameters.m_PadTop == 0);
+ CHECK(queueDescriptor.m_Parameters.m_PadBottom == 0);
+ CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
+
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+ CHECK((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo(weightShape, DataType)));
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename LstmWorkload>
+std::unique_ptr<LstmWorkload> CreateLstmWorkloadTest(armnn::IWorkloadFactory& factory, armnn::Graph& graph)
+{
+ // This parameter setting is for withCifgWithPeepholeNoProjection
+ LstmDescriptor layerDesc;
+ layerDesc.m_ActivationFunc = 4;
+ layerDesc.m_ClippingThresCell = 0.0f;
+ layerDesc.m_ClippingThresProj = 0.0f;
+ layerDesc.m_CifgEnabled = true;
+ layerDesc.m_PeepholeEnabled = true;
+ layerDesc.m_ProjectionEnabled = false;
+
+ LstmLayer* const layer = graph.AddLayer<LstmLayer>(layerDesc, "layer");
+ unsigned int batchSize = 2;
+ unsigned int inputSize = 2;
+ unsigned int numUnits = 4;
+ unsigned int outputSize = 4;
+
+ layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({ numUnits, inputSize }, DataType::Float32));
+ layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({ numUnits, inputSize }, DataType::Float32));
+ layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({ numUnits, inputSize }, DataType::Float32));
+ layer->m_BasicParameters.m_RecurrentToForgetWeights = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({ numUnits, outputSize }, DataType::Float32));
+ layer->m_BasicParameters.m_RecurrentToCellWeights = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({ numUnits, outputSize }, DataType::Float32));
+ layer->m_BasicParameters.m_RecurrentToOutputWeights = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({ numUnits, outputSize }, DataType::Float32));
+ layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({ numUnits }, DataType::Float32));
+ layer->m_BasicParameters.m_CellBias = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({ numUnits }, DataType::Float32));
+ layer->m_BasicParameters.m_OutputGateBias = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({ numUnits }, DataType::Float32));
+
+ layer->m_BasicParameters.m_InputToForgetWeights->Allocate();
+ layer->m_BasicParameters.m_InputToCellWeights->Allocate();
+ layer->m_BasicParameters.m_InputToOutputWeights->Allocate();
+ layer->m_BasicParameters.m_RecurrentToForgetWeights->Allocate();
+ layer->m_BasicParameters.m_RecurrentToCellWeights->Allocate();
+ layer->m_BasicParameters.m_RecurrentToOutputWeights->Allocate();
+ layer->m_BasicParameters.m_ForgetGateBias->Allocate();
+ layer->m_BasicParameters.m_CellBias->Allocate();
+ layer->m_BasicParameters.m_OutputGateBias->Allocate();
+
+
+ if (layerDesc.m_PeepholeEnabled)
+ {
+ layer->m_PeepholeParameters.m_CellToForgetWeights = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({ numUnits }, DataType::Float32));
+ layer->m_PeepholeParameters.m_CellToOutputWeights = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({ numUnits }, DataType::Float32));
+ layer->m_PeepholeParameters.m_CellToForgetWeights->Allocate();
+ layer->m_PeepholeParameters.m_CellToOutputWeights->Allocate();
+ }
+
+ // create input and output layers
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const outputStateIn = graph.AddLayer<InputLayer>(1, "outputStateIn");
+ Layer* const cellStateIn = graph.AddLayer<InputLayer>(2, "cellStateIn");
+ Layer* const scratchBuffer = graph.AddLayer<OutputLayer>(0, "scratchBuffer");
+ Layer* const outputStateOut = graph.AddLayer<OutputLayer>(1, "outputStateOut");
+ Layer* const cellStateOut = graph.AddLayer<OutputLayer>(2, "cellStateOut");
+ Layer* const output = graph.AddLayer<OutputLayer>(3, "output");
+
+ // connect up
+ armnn::TensorInfo lstmTensorInfo1({ batchSize, inputSize }, DataType::Float32);
+ armnn::TensorInfo lstmTensorInfo2({ batchSize, numUnits}, DataType::Float32);
+ armnn::TensorInfo lstmTensorInfo3({ batchSize, outputSize }, DataType::Float32);
+ armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * (layerDesc.m_CifgEnabled ? 3 : 4) },
+ DataType::Float32);
+ Connect(input, layer, lstmTensorInfo1, 0, 0);
+ Connect(cellStateIn, layer, lstmTensorInfo2, 0, 1);
+ Connect(outputStateIn, layer, lstmTensorInfo3, 0, 2);
+ Connect(layer, scratchBuffer, lstmTensorInfoScratchBuff, 0, 0);
+ Connect(layer, outputStateOut, lstmTensorInfo3, 1, 0);
+ Connect(layer, cellStateOut, lstmTensorInfo2, 2, 0);
+ Connect(layer, output, lstmTensorInfo3, 3, 0);
+
+ CreateTensorHandles(graph, factory);
+
+ // make the workload and check it
+ auto workload = MakeAndCheckWorkload<LstmWorkload>(*layer, factory);
+ LstmQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Parameters.m_ActivationFunc == 4);
+ CHECK(queueDescriptor.m_Parameters.m_ClippingThresCell == 0.0f);
+ CHECK(queueDescriptor.m_Parameters.m_ClippingThresProj == 0.0f);
+ CHECK(queueDescriptor.m_Inputs.size() == 3);
+ CHECK(queueDescriptor.m_Outputs.size() == 4);
+
+ CHECK((queueDescriptor.m_InputToForgetWeights->GetTensorInfo() == TensorInfo({ numUnits, inputSize },
+ DataType::Float32)));
+ CHECK((queueDescriptor.m_OutputGateBias->GetTensorInfo() == TensorInfo({ numUnits },
+ DataType::Float32)));
+ CHECK((queueDescriptor.m_CellBias->GetTensorInfo() == TensorInfo({ numUnits }, DataType::Float32)));
+ return workload;
+}
+
+template <typename QuantizedLstmWorkload>
+std::unique_ptr<QuantizedLstmWorkload> CreateQuantizedLstmWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ auto layer = graph.AddLayer<QuantizedLstmLayer>("quantizedLstmlayer");
+ unsigned int numBatches = 2;
+ unsigned int inputSize = 2;
+ unsigned int outputSize = 4;
+
+ // Scale/Offset for input/output, cellState In/Out, weights, bias
+ float inputOutputScale = 0.0078125f;
+ int32_t inputOutputOffset = 128;
+
+ float cellStateScale = 0.00048828125f;
+ int32_t cellStateOffset = 0;
+
+ float weightsScale = 0.00408021f;
+ int32_t weightsOffset = 100;
+
+ float biasScale = 3.1876640625e-05f;
+ int32_t biasOffset = 0;
+
+ // Weights and bias tensor and quantization info
+ armnn::TensorInfo inputWeightsInfo({outputSize, inputSize},
+ armnn::DataType::QAsymmU8,
+ weightsScale,
+ weightsOffset);
+
+ armnn::TensorInfo recurrentWeightsInfo({outputSize, outputSize},
+ armnn::DataType::QAsymmU8,
+ weightsScale,
+ weightsOffset);
+
+ armnn::TensorInfo biasInfo({outputSize},
+ armnn::DataType::Signed32,
+ biasScale,
+ biasOffset);
+
+ // Weights and bias
+ layer->m_QuantizedLstmParameters.m_InputToInputWeights =
+ std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
+ layer->m_QuantizedLstmParameters.m_InputToForgetWeights =
+ std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
+ layer->m_QuantizedLstmParameters.m_InputToCellWeights =
+ std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
+ layer->m_QuantizedLstmParameters.m_InputToOutputWeights =
+ std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
+
+ layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights =
+ std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
+ layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights =
+ std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
+ layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights =
+ std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
+ layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights =
+ std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
+
+ layer->m_QuantizedLstmParameters.m_InputGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);
+ layer->m_QuantizedLstmParameters.m_ForgetGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);
+ layer->m_QuantizedLstmParameters.m_CellBias = std::make_unique<ScopedTensorHandle>(biasInfo);
+ layer->m_QuantizedLstmParameters.m_OutputGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);
+
+ // Allocate weights and bias
+ layer->m_QuantizedLstmParameters.m_InputToInputWeights->Allocate();
+ layer->m_QuantizedLstmParameters.m_InputToForgetWeights->Allocate();
+ layer->m_QuantizedLstmParameters.m_InputToCellWeights->Allocate();
+ layer->m_QuantizedLstmParameters.m_InputToOutputWeights->Allocate();
+
+ layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights->Allocate();
+ layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights->Allocate();
+ layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights->Allocate();
+ layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights->Allocate();
+
+ layer->m_QuantizedLstmParameters.m_InputGateBias->Allocate();
+ layer->m_QuantizedLstmParameters.m_ForgetGateBias->Allocate();
+ layer->m_QuantizedLstmParameters.m_CellBias->Allocate();
+ layer->m_QuantizedLstmParameters.m_OutputGateBias->Allocate();
+
+ // Create input and output layers
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const cellStateIn = graph.AddLayer<InputLayer>(1, "cellStateIn");
+ Layer* const outputStateIn = graph.AddLayer<InputLayer>(2, "outputStateIn");
+
+ Layer* const cellStateOut = graph.AddLayer<OutputLayer>(0, "cellStateOut");
+ Layer* const outputStateOut = graph.AddLayer<OutputLayer>(1, "outputStateOut");
+
+ // Input/output tensor info and quantization info
+ armnn::TensorInfo inputInfo({numBatches , inputSize},
+ armnn::DataType::QAsymmU8,
+ inputOutputScale,
+ inputOutputOffset);
+
+ armnn::TensorInfo cellStateInfo({numBatches , outputSize},
+ armnn::DataType::QSymmS16,
+ cellStateScale,
+ cellStateOffset);
+
+ armnn::TensorInfo outputStateInfo({numBatches , outputSize},
+ armnn::DataType::QAsymmU8,
+ inputOutputScale,
+ inputOutputOffset);
+
+ // Connect input/output slots
+ Connect(input, layer, inputInfo, 0, 0);
+ Connect(cellStateIn, layer, cellStateInfo, 0, 1);
+ Connect(outputStateIn, layer, outputStateInfo, 0, 2);
+
+ Connect(layer, cellStateOut, cellStateInfo, 0, 0);
+ Connect(layer, outputStateOut, outputStateInfo, 1, 0);
+
+ CreateTensorHandles(graph, factory);
+
+ // Create workload and check layer support
+ auto workload = MakeAndCheckWorkload<QuantizedLstmWorkload>(*layer, factory);
+ QuantizedLstmQueueDescriptor queueDescriptor = workload->GetData();
+
+ // Validate input/output sizes
+ CHECK(queueDescriptor.m_Inputs.size() == 3);
+ CHECK(queueDescriptor.m_Outputs.size() == 2);
+
+ // Validate weight tensor info
+ CHECK((queueDescriptor.m_InputToInputWeights->GetTensorInfo() == inputWeightsInfo));
+ CHECK((queueDescriptor.m_InputToForgetWeights->GetTensorInfo() == inputWeightsInfo));
+ CHECK((queueDescriptor.m_InputToCellWeights->GetTensorInfo() == inputWeightsInfo));
+ CHECK((queueDescriptor.m_InputToOutputWeights->GetTensorInfo() == inputWeightsInfo));
+
+ CHECK((queueDescriptor.m_RecurrentToInputWeights->GetTensorInfo() == recurrentWeightsInfo));
+ CHECK((queueDescriptor.m_RecurrentToForgetWeights->GetTensorInfo() == recurrentWeightsInfo));
+ CHECK((queueDescriptor.m_RecurrentToCellWeights->GetTensorInfo() == recurrentWeightsInfo));
+ CHECK((queueDescriptor.m_RecurrentToOutputWeights->GetTensorInfo() == recurrentWeightsInfo));
+
+ CHECK((queueDescriptor.m_InputGateBias->GetTensorInfo() == biasInfo));
+ CHECK((queueDescriptor.m_ForgetGateBias->GetTensorInfo() == biasInfo));
+ CHECK((queueDescriptor.m_CellBias->GetTensorInfo() == biasInfo));
+ CHECK((queueDescriptor.m_OutputGateBias->GetTensorInfo() == biasInfo));
+
+ return workload;
+}
+
+template <typename QLstmWorkload>
+std::unique_ptr<QLstmWorkload> CreateQLstmWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ QLstmDescriptor layerDesc;
+ layerDesc.m_CifgEnabled = true;
+ layerDesc.m_PeepholeEnabled = false;
+ layerDesc.m_ProjectionEnabled = false;
+ layerDesc.m_LayerNormEnabled = true;
+
+ layerDesc.m_CellClip = 0.0f;
+ layerDesc.m_ProjectionClip = 0.0f;
+
+ layerDesc.m_HiddenStateZeroPoint = 0;
+ layerDesc.m_HiddenStateScale = 0.007f;
+
+ layerDesc.m_InputIntermediateScale = 0.007059f;
+ layerDesc.m_ForgetIntermediateScale = 0.007812f;
+ layerDesc.m_CellIntermediateScale = 0.007059f;
+ layerDesc.m_OutputIntermediateScale = 0.007812f;
+
+ QLstmLayer* const layer = graph.AddLayer<QLstmLayer>(layerDesc, "qLstm");
+
+ unsigned int numBatches = 2;
+ unsigned int inputSize = 4;
+ unsigned int numUnits = 4;
+ unsigned int outputSize = 4;
+
+ // Scale/Offset quantization info
+ float inputScale = 0.0078125f;
+ int32_t inputOffset = 0;
+
+ // if (!projectionEnabled) outputScale == hiddenStateScale
+ float outputScale = layerDesc.m_HiddenStateScale;
+ int32_t outputOffset = layerDesc.m_HiddenStateZeroPoint;
+
+ float cellStateScale = 3.05176e-05f;
+ int32_t cellStateOffset = 0;
+
+ float weightsScale = 0.00784314f;
+ int32_t weightsOffset = 0;
+
+ float layerNormScale = 3.05182e-05f;
+ int32_t layerNormOffset = 0;
+
+ float biasScale = layerNormScale / 1024;
+ int32_t biasOffset = 0;
+
+ // Weights and bias tensor and quantization info
+ armnn::TensorInfo inputWeightsInfo({outputSize, inputSize},
+ armnn::DataType::QSymmS8,
+ weightsScale,
+ weightsOffset);
+
+ armnn::TensorInfo recurrentWeightsInfo({outputSize, outputSize},
+ armnn::DataType::QSymmS8,
+ weightsScale,
+ weightsOffset);
+
+ armnn::TensorInfo biasInfo({outputSize}, armnn::DataType::Signed32, biasScale, biasOffset);
+
+ armnn::TensorInfo layerNormWeightsInfo({numUnits}, armnn::DataType::QSymmS16, layerNormScale, layerNormOffset);
+
+ // Create and allocate tensors
+ layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
+ layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
+ layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<ScopedTensorHandle>(inputWeightsInfo);
+
+ layer->m_BasicParameters.m_RecurrentToForgetWeights =
+ std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
+ layer->m_BasicParameters.m_RecurrentToCellWeights =
+ std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
+ layer->m_BasicParameters.m_RecurrentToOutputWeights =
+ std::make_unique<ScopedTensorHandle>(recurrentWeightsInfo);
+
+ layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);
+ layer->m_BasicParameters.m_CellBias = std::make_unique<ScopedTensorHandle>(biasInfo);
+ layer->m_BasicParameters.m_OutputGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);
+
+ layer->m_LayerNormParameters.m_ForgetLayerNormWeights =
+ std::make_unique<ScopedTensorHandle>(layerNormWeightsInfo);
+ layer->m_LayerNormParameters.m_CellLayerNormWeights =
+ std::make_unique<ScopedTensorHandle>(layerNormWeightsInfo);
+ layer->m_LayerNormParameters.m_OutputLayerNormWeights =
+ std::make_unique<ScopedTensorHandle>(layerNormWeightsInfo);
+
+ layer->m_BasicParameters.m_InputToForgetWeights->Allocate();
+ layer->m_BasicParameters.m_InputToCellWeights->Allocate();
+ layer->m_BasicParameters.m_InputToOutputWeights->Allocate();
+
+ layer->m_BasicParameters.m_RecurrentToForgetWeights->Allocate();
+ layer->m_BasicParameters.m_RecurrentToCellWeights->Allocate();
+ layer->m_BasicParameters.m_RecurrentToOutputWeights->Allocate();
+
+ layer->m_BasicParameters.m_ForgetGateBias->Allocate();
+ layer->m_BasicParameters.m_CellBias->Allocate();
+ layer->m_BasicParameters.m_OutputGateBias->Allocate();
+
+ layer->m_LayerNormParameters.m_ForgetLayerNormWeights->Allocate();
+ layer->m_LayerNormParameters.m_CellLayerNormWeights->Allocate();
+ layer->m_LayerNormParameters.m_OutputLayerNormWeights->Allocate();
+
+ // Input and output layers
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const outputStateIn = graph.AddLayer<InputLayer>(1, "outputStateIn");
+ Layer* const cellStateIn = graph.AddLayer<InputLayer>(2, "cellStateIn");
+
+ Layer* const outputStateOut = graph.AddLayer<OutputLayer>(0, "outputStateOut");
+ Layer* const cellStateOut = graph.AddLayer<OutputLayer>(1, "cellStateOut");
+ Layer* const output = graph.AddLayer<OutputLayer>(2, "output");
+
+ // Input/Output tensor info
+ armnn::TensorInfo inputInfo({numBatches , inputSize},
+ armnn::DataType::QAsymmS8,
+ inputScale,
+ inputOffset);
+
+ armnn::TensorInfo cellStateInfo({numBatches , numUnits},
+ armnn::DataType::QSymmS16,
+ cellStateScale,
+ cellStateOffset);
+
+ armnn::TensorInfo outputStateInfo({numBatches , outputSize},
+ armnn::DataType::QAsymmS8,
+ outputScale,
+ outputOffset);
+
+ // Connect layers to slots
+ Connect(input, layer, inputInfo, 0, 0);
+ Connect(outputStateIn, layer, outputStateInfo, 0, 1);
+ Connect(cellStateIn, layer, cellStateInfo, 0, 2);
+
+ Connect(layer, outputStateOut, outputStateInfo, 0, 0);
+ Connect(layer, cellStateOut, cellStateInfo, 1, 0);
+ Connect(layer, output, outputStateInfo, 2, 0);
+
+ CreateTensorHandles(graph, factory);
+
+ // Create and check workload
+ auto workload = MakeAndCheckWorkload<QLstmWorkload>(*layer, factory);
+ QLstmQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Parameters.m_CellClip == 0.0f);
+ CHECK(queueDescriptor.m_Parameters.m_ProjectionClip == 0.0f);
+ CHECK(queueDescriptor.m_Inputs.size() == 3);
+ CHECK(queueDescriptor.m_Outputs.size() == 3);
+
+ CHECK((queueDescriptor.m_InputToForgetWeights->GetTensorInfo() == inputWeightsInfo));
+ CHECK((queueDescriptor.m_InputToCellWeights->GetTensorInfo() == inputWeightsInfo));
+ CHECK((queueDescriptor.m_InputToOutputWeights->GetTensorInfo() == inputWeightsInfo));
+
+ CHECK((queueDescriptor.m_RecurrentToForgetWeights->GetTensorInfo() == recurrentWeightsInfo));
+ CHECK((queueDescriptor.m_RecurrentToCellWeights->GetTensorInfo() == recurrentWeightsInfo));
+ CHECK((queueDescriptor.m_RecurrentToOutputWeights->GetTensorInfo() == recurrentWeightsInfo));
+
+ CHECK((queueDescriptor.m_ForgetGateBias->GetTensorInfo() == biasInfo));
+ CHECK((queueDescriptor.m_CellBias->GetTensorInfo() == biasInfo));
+ CHECK((queueDescriptor.m_OutputGateBias->GetTensorInfo() == biasInfo));
+
+ return workload;
+}
+
+template <typename Convolution2dWorkload, armnn::DataType DataType>
+std::unique_ptr<Convolution2dWorkload> CreateDirectConvolution2dWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ // Creates the layer we're testing.
+ Convolution2dDescriptor layerDesc;
+ layerDesc.m_PadLeft = 1;
+ layerDesc.m_PadRight = 1;
+ layerDesc.m_PadTop = 1;
+ layerDesc.m_PadBottom = 1;
+ layerDesc.m_StrideX = 1;
+ layerDesc.m_StrideY = 1;
+ layerDesc.m_BiasEnabled = true;
+
+ Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");
+
+ float inputsQScale = DataType == armnn::DataType::QAsymmU8 ? 1.0f : 0.0;
+ float outputQScale = DataType == armnn::DataType::QAsymmU8 ? 2.0f : 0.0;
+
+ layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({ 2, 3, 3, 3 }, DataType, inputsQScale));
+ layer->m_Bias = std::make_unique<ScopedTensorHandle>
+ (TensorInfo({2}, GetBiasDataType(DataType), inputsQScale));
+ layer->m_Weight->Allocate();
+ layer->m_Bias->Allocate();
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ Connect(input, layer, TensorInfo({2, 3, 6, 6}, DataType, inputsQScale));
+ Connect(layer, output, TensorInfo({2, 2, 6, 6}, DataType, outputQScale));
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory);
+
+ Convolution2dQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Parameters.m_StrideX == 1);
+ CHECK(queueDescriptor.m_Parameters.m_StrideY == 1);
+ CHECK(queueDescriptor.m_Parameters.m_PadLeft == 1);
+ CHECK(queueDescriptor.m_Parameters.m_PadRight == 1);
+ CHECK(queueDescriptor.m_Parameters.m_PadTop == 1);
+ CHECK(queueDescriptor.m_Parameters.m_PadBottom == 1);
+ CHECK(queueDescriptor.m_Parameters.m_BiasEnabled == true);
+
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+ CHECK((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo({2, 3, 3, 3},
+ DataType, inputsQScale)));
+ CHECK((queueDescriptor.m_Bias->GetTensorInfo()
+ == TensorInfo({2}, GetBiasDataType(DataType), inputsQScale)));
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename DepthwiseConvolution2dFloat32Workload, armnn::DataType DataType>
+std::unique_ptr<DepthwiseConvolution2dFloat32Workload> CreateDepthwiseConvolution2dWorkloadTest(
+ armnn::IWorkloadFactory& factory, armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW)
+{
+ // Creates the layer we're testing.
+ DepthwiseConvolution2dDescriptor layerDesc;
+ layerDesc.m_PadLeft = 1;
+ layerDesc.m_PadRight = 2;
+ layerDesc.m_PadTop = 1;
+ layerDesc.m_PadBottom = 2;
+ layerDesc.m_StrideX = 1;
+ layerDesc.m_StrideY = 1;
+ layerDesc.m_BiasEnabled = false;
+ layerDesc.m_DataLayout = dataLayout;
+
+ DepthwiseConvolution2dLayer* const layer = graph.AddLayer<DepthwiseConvolution2dLayer>(layerDesc, "layer");
+
+ layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({1, 4, 4, 2}, DataType)); // [ 1, H, W, I*M ]
+ layer->m_Weight->Allocate();
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ TensorShape inputShape = (dataLayout == DataLayout::NCHW) ?
+ TensorShape{ 2, 2, 5, 5 } : TensorShape{ 2, 5, 5, 2 };
+ TensorShape outputShape = (dataLayout == DataLayout::NCHW) ?
+ TensorShape{ 2, 2, 5, 5 } : TensorShape{ 2, 5, 5, 2 };
+
+ // Connects up.
+ Connect(input, layer, TensorInfo(inputShape, DataType));
+ Connect(layer, output, TensorInfo(outputShape, DataType));
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<DepthwiseConvolution2dFloat32Workload>(*layer, factory);
+
+ DepthwiseConvolution2dQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Parameters.m_StrideX == 1);
+ CHECK(queueDescriptor.m_Parameters.m_StrideY == 1);
+ CHECK(queueDescriptor.m_Parameters.m_PadLeft == 1);
+ CHECK(queueDescriptor.m_Parameters.m_PadRight == 2);
+ CHECK(queueDescriptor.m_Parameters.m_PadTop == 1);
+ CHECK(queueDescriptor.m_Parameters.m_PadBottom == 2);
+ CHECK(queueDescriptor.m_Parameters.m_BiasEnabled == false);
+ CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
+
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+ CHECK((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo({1, 4, 4, 2}, DataType)));
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename FullyConnectedWorkload, armnn::DataType DataType>
+std::unique_ptr<FullyConnectedWorkload> CreateFullyConnectedWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ // Creates the layer we're testing.
+ FullyConnectedDescriptor layerDesc;
+ layerDesc.m_BiasEnabled = false;
+ layerDesc.m_TransposeWeightMatrix = true;
+
+ FullyConnectedLayer* const layer = graph.AddLayer<FullyConnectedLayer>(layerDesc, "layer");
+
+ float inputsQScale = DataType == armnn::DataType::QAsymmU8 ? 1.0f : 0.0;
+ float outputQScale = DataType == armnn::DataType::QAsymmU8 ? 2.0f : 0.0;
+
+ // As optimization isn't run member variables need to be updated.
+ layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({7, 20}, DataType, inputsQScale, 0));
+ layer->m_Weight->Allocate();
+
+ armnn::TensorInfo weightsTensorInfo({7, 20}, DataType, inputsQScale);
+ weightsTensorInfo.SetConstant();
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ auto const weights = graph.AddLayer<ConstantLayer>("weights");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ weights->m_LayerOutput = std::make_unique<ScopedTensorHandle>(weightsTensorInfo);
+ weights->m_LayerOutput->Allocate();
+
+ // Connects up.
+ Connect(input, layer, TensorInfo({3, 1, 4, 5}, DataType, inputsQScale), 0, 0);
+ Connect(weights, layer, weightsTensorInfo, 0, 1);
+ Connect(layer, output, TensorInfo({3, 7}, DataType, outputQScale));
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<FullyConnectedWorkload>(*layer, factory);
+
+ FullyConnectedQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Parameters.m_TransposeWeightMatrix == true);
+
+ CHECK(queueDescriptor.m_Inputs.size() == 2);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename FullyConnectedWorkload, armnn::DataType DataType>
+std::unique_ptr<FullyConnectedWorkload> CreateFullyConnectedWithBlobWorkloadTest
+ (armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ // Creates 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 = DataType == armnn::DataType::QAsymmU8 ? 1.0f : 0.0;
+ float outputQScale = DataType == armnn::DataType::QAsymmU8 ? 2.0f : 0.0;
+
+ // As optimization isn't run member variables need to be updated.
+ layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({7, 20}, DataType, inputsQScale, 0));
+ layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({7}, GetBiasDataType(DataType), inputsQScale));
+ layer->m_Weight->Allocate();
+ layer->m_Bias->Allocate();
+
+ armnn::TensorInfo weightsTensorInfo({7, 20}, DataType, inputsQScale);
+ armnn::TensorInfo biasesTensorInfo({7}, GetBiasDataType(DataType), inputsQScale);
+ weightsTensorInfo.SetConstant();
+ biasesTensorInfo.SetConstant();
+
+ auto activationDesc = std::make_shared<ActivationDescriptor>();
+ activationDesc->m_A = 10.0f;
+ activationDesc->m_B = 5.0f;
+ activationDesc->m_Function = armnn::ActivationFunction::BoundedReLu;
+
+ layer->SetAdditionalInfoForObject(activationDesc);
+
+ // Check that the additional information can be queried from the layer
+ std::shared_ptr<ActivationDescriptor> activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(activationDescPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(static_cast<ActivationFunction>(activationDescPtr->m_Function) ==
+ armnn::ActivationFunction::BoundedReLu);
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ auto const weights = graph.AddLayer<ConstantLayer>("weights");
+ auto const biases = graph.AddLayer<ConstantLayer>("biases");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ weights->m_LayerOutput = std::make_unique<ScopedTensorHandle>(weightsTensorInfo);
+ weights->m_LayerOutput->Allocate();
+ biases->m_LayerOutput = std::make_unique<ScopedTensorHandle>(biasesTensorInfo);
+ biases->m_LayerOutput->Allocate();
+
+ // Connects up.
+ Connect(input, layer, TensorInfo({3, 1, 4, 5}, DataType, inputsQScale), 0, 0);
+ Connect(weights, layer, weightsTensorInfo, 0, 1);
+ Connect(biases, layer, biasesTensorInfo, 0, 2);
+ Connect(layer, output, TensorInfo({3, 7}, DataType, outputQScale));
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<FullyConnectedWorkload>(*layer, factory);
+
+ FullyConnectedQueueDescriptor queueDescriptor = workload->GetData();
+
+ const ActivationDescriptor* queueDescBlobPtr = queueDescriptor.GetAdditionalInformation<ActivationDescriptor>();
+ IgnoreUnused(queueDescBlobPtr);
+
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_A) == 10.0f);
+ ARMNN_ASSERT(static_cast<float>(queueDescBlobPtr->m_B) == 5.0f);
+ ARMNN_ASSERT(
+ static_cast<ActivationFunction>(queueDescBlobPtr->m_Function) == armnn::ActivationFunction::BoundedReLu
+ );
+
+ CHECK(queueDescriptor.m_Parameters.m_BiasEnabled == true);
+ CHECK(queueDescriptor.m_Parameters.m_TransposeWeightMatrix == true);
+ CHECK(queueDescriptor.m_Inputs.size() == 3);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename FullyConnectedWorkload, armnn::DataType DataType>
+std::unique_ptr<FullyConnectedWorkload> CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest
+ (armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ // Creates the layer we're testing.
+ FullyConnectedDescriptor layerDesc;
+ layerDesc.m_BiasEnabled = true;
+ layerDesc.m_TransposeWeightMatrix = true;
+ layerDesc.m_ConstantWeights = false;
+
+ FullyConnectedLayer* const layer = graph.AddLayer<FullyConnectedLayer>(layerDesc, "layer");
+
+ float inputsQScale = DataType == armnn::DataType::QAsymmU8 ? 1.0f : 0.0;
+ float outputQScale = DataType == armnn::DataType::QAsymmU8 ? 2.0f : 0.0;
+
+ // Creates extra layers with weights and biases as input layers.
+ Layer* const input = graph.AddLayer<InputLayer>(1, "input");
+ Layer* const weights = graph.AddLayer<InputLayer>(2, "weights");
+ Layer* const biases = graph.AddLayer<InputLayer>(3, "biases");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ Connect(input, layer, TensorInfo({3, 1, 4, 5}, DataType, inputsQScale), 0, 0);
+ Connect(weights, layer, TensorInfo({7, 20}, DataType, inputsQScale), 0, 1);
+ Connect(biases, layer, TensorInfo({7}, GetBiasDataType(DataType), inputsQScale), 0, 2);
+ Connect(layer, output, TensorInfo({3, 7}, DataType, outputQScale));
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<FullyConnectedWorkload>(*layer, factory);
+
+ FullyConnectedQueueDescriptor queueDescriptor = workload->GetData();
+
+ CHECK(queueDescriptor.m_Parameters.m_BiasEnabled == true);
+ CHECK(queueDescriptor.m_Parameters.m_TransposeWeightMatrix == true);
+ CHECK(queueDescriptor.m_Parameters.m_ConstantWeights == false);
+ CHECK(queueDescriptor.m_Inputs.size() == 3);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+
+template <typename NormalizationWorkload, armnn::DataType DataType>
+std::unique_ptr<NormalizationWorkload> CreateNormalizationWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph,
+ DataLayout dataLayout = DataLayout::NCHW)
+{
+ // Creates the layer we're testing.
+ NormalizationDescriptor layerDesc;
+ layerDesc.m_NormChannelType = NormalizationAlgorithmChannel::Across;
+ layerDesc.m_NormMethodType = NormalizationAlgorithmMethod::LocalBrightness;
+ layerDesc.m_NormSize = 3;
+ layerDesc.m_Alpha = 0.5f;
+ layerDesc.m_Beta = -1.0f;
+ layerDesc.m_K = 0.2f;
+ layerDesc.m_DataLayout = dataLayout;
+
+ NormalizationLayer* layer = graph.AddLayer<NormalizationLayer>(layerDesc, "layer");
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ TensorShape inputShape = (dataLayout == DataLayout::NCHW) ?
+ TensorShape{ 3, 5, 5, 1 } : TensorShape{ 3, 1, 5, 5 };
+ TensorShape outputShape = (dataLayout == DataLayout::NCHW) ?
+ TensorShape{ 3, 5, 5, 1 } : TensorShape{ 3, 1, 5, 5 };
+
+ // Connects up.
+ armnn::TensorInfo inputTensorInfo(inputShape, DataType);
+ armnn::TensorInfo outputTensorInfo(outputShape, DataType);
+ Connect(input, layer, inputTensorInfo);
+ Connect(layer, output, outputTensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<NormalizationWorkload>(*layer, factory);
+
+ NormalizationQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK((queueDescriptor.m_Parameters.m_NormChannelType == NormalizationAlgorithmChannel::Across));
+ CHECK((queueDescriptor.m_Parameters.m_NormMethodType == NormalizationAlgorithmMethod::LocalBrightness));
+ CHECK(queueDescriptor.m_Parameters.m_NormSize == 3);
+ CHECK(queueDescriptor.m_Parameters.m_Alpha == 0.5f);
+ CHECK(queueDescriptor.m_Parameters.m_Beta == -1.0f);
+ CHECK(queueDescriptor.m_Parameters.m_K == 0.2f);
+ CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
+
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename Pooling2dWorkload, armnn::DataType DataType>
+std::unique_ptr<Pooling2dWorkload> CreatePooling2dWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph,
+ DataLayout dataLayout = DataLayout::NCHW)
+{
+ // Creates the layer we're testing.
+ Pooling2dDescriptor layerDesc;
+ layerDesc.m_PoolType = PoolingAlgorithm::Average;
+ layerDesc.m_PoolWidth = 3;
+ layerDesc.m_PoolHeight = 3;
+ layerDesc.m_PadLeft = 2;
+ layerDesc.m_PadRight = 2;
+ layerDesc.m_PadTop = 1;
+ layerDesc.m_PadBottom = 1;
+ layerDesc.m_StrideX = 2;
+ layerDesc.m_StrideY = 3;
+ layerDesc.m_OutputShapeRounding = OutputShapeRounding::Floor;
+ layerDesc.m_DataLayout = dataLayout;
+
+ Pooling2dLayer* const layer = graph.AddLayer<Pooling2dLayer>(layerDesc, "layer");
+
+ // Create extra layers
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{3, 2, 5, 5} : TensorShape{3, 5, 5, 2};
+ TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{3, 2, 2, 4} : TensorShape{3, 2, 4, 2};
+
+ // Connect up
+ Connect(input, layer, TensorInfo(inputShape, DataType));
+ Connect(layer, output, TensorInfo(outputShape, DataType));
+ CreateTensorHandles(graph, factory);
+
+ // Make the workload and checks it
+ auto workload = MakeAndCheckWorkload<Pooling2dWorkload>(*layer, factory);
+
+ Pooling2dQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK((queueDescriptor.m_Parameters.m_PoolType == PoolingAlgorithm::Average));
+ CHECK((queueDescriptor.m_Parameters.m_OutputShapeRounding == OutputShapeRounding::Floor));
+ CHECK(queueDescriptor.m_Parameters.m_PoolWidth == 3);
+ CHECK(queueDescriptor.m_Parameters.m_PoolHeight == 3);
+ CHECK(queueDescriptor.m_Parameters.m_StrideX == 2);
+ CHECK(queueDescriptor.m_Parameters.m_StrideY == 3);
+ CHECK(queueDescriptor.m_Parameters.m_PadLeft == 2);
+ CHECK(queueDescriptor.m_Parameters.m_PadRight == 2);
+ CHECK(queueDescriptor.m_Parameters.m_PadTop == 1);
+ CHECK(queueDescriptor.m_Parameters.m_PadBottom == 1);
+ CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
+
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Return so we can do extra, backend-specific tests
+ return workload;
+}
+
+template <typename SoftmaxWorkload, armnn::DataType DataType>
+std::unique_ptr<SoftmaxWorkload> CreateSoftmaxWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ // Create the layer we're testing.
+ SoftmaxDescriptor softmaxDescriptor;
+ // Set Axis to -1 if CL or Neon until further Axes are supported.
+ if (factory.GetBackendId() == armnn::Compute::CpuAcc || factory.GetBackendId() == armnn::Compute::GpuAcc)
+ {
+ softmaxDescriptor.m_Axis = -1;
+ }
+
+ Layer* const layer = graph.AddLayer<SoftmaxLayer>(softmaxDescriptor, "layer");
+ // Create extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connect up
+ armnn::TensorInfo tensorInfo({4, 1}, DataType);
+ if (DataType == armnn::DataType::QAsymmU8)
+ {
+ tensorInfo.SetQuantizationOffset(0);
+ tensorInfo.SetQuantizationScale(1.f / 256);
+ }
+ else if (DataType == armnn::DataType::QAsymmS8)
+ {
+ tensorInfo.SetQuantizationOffset(-128);
+ tensorInfo.SetQuantizationScale(1.f / 256);
+ }
+
+ Connect(input, layer, tensorInfo);
+ Connect(layer, output, tensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Make the workload and checks it.
+ auto workload = MakeAndCheckWorkload<SoftmaxWorkload>(*layer, factory);
+
+ SoftmaxQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Return so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template<typename SplitterWorkload, armnn::DataType DataType>
+std::unique_ptr<SplitterWorkload>
+ CreateSplitterWorkloadTest(armnn::IWorkloadFactory& factory, armnn::Graph& graph)
+{
+ // Create the layer we're testing.
+ // NOTE: need three dimensions channels, height/y, width/x because the Compute
+ // library restricts subtensors to have the same x and y dimensions as
+ // their parent tensors, and therefore the origin on the x and y dimension
+ // has to be zero for any view. So we need a third dimension to split...
+ // NOTE: arguments are: number of views, number of dimensions.
+ ViewsDescriptor layerDesc(3, 3);
+ // NOTE: arguments are: view, dimension, value.
+ layerDesc.SetViewOriginCoord(0, 0, 0);
+ layerDesc.SetViewOriginCoord(1, 0, 1);
+ layerDesc.SetViewOriginCoord(2, 0, 3);
+
+ Layer* const layer = graph.AddLayer<SplitterLayer>(layerDesc, "layer");
+
+ // Adds extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output0 = graph.AddLayer<OutputLayer>(0, "output0");
+ Layer* const output1 = graph.AddLayer<OutputLayer>(1, "output1");
+ Layer* const output2 = graph.AddLayer<OutputLayer>(2, "output2");
+
+ // Connects up.
+ armnn::TensorInfo tensorInfo({5, 7, 7}, DataType);
+ Connect(input, layer, tensorInfo);
+
+ armnn::TensorInfo output0Info({1, 7, 7}, DataType);
+ armnn::TensorInfo output1Info({2, 7, 7}, DataType);
+ armnn::TensorInfo output2Info({2, 7, 7}, DataType);
+
+ Connect(layer, output0, output0Info, 0, 0);
+ Connect(layer, output1, output1Info, 1, 0);
+ Connect(layer, output2, output2Info, 2, 0);
+
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<SplitterWorkload>(*layer, factory);
+
+ SplitterQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 3);
+ CHECK(queueDescriptor.m_ViewOrigins.size() == 3);
+
+ CHECK(queueDescriptor.m_ViewOrigins[0].m_Origin[0] == 0);
+ CHECK(queueDescriptor.m_ViewOrigins[1].m_Origin[0] == 1);
+ CHECK(queueDescriptor.m_ViewOrigins[2].m_Origin[0] == 3);
+ CHECK(queueDescriptor.m_ViewOrigins[0].m_Origin[1] == 0);
+ CHECK(queueDescriptor.m_ViewOrigins[1].m_Origin[1] == 0);
+ CHECK(queueDescriptor.m_ViewOrigins[2].m_Origin[1] == 0);
+ CHECK(queueDescriptor.m_ViewOrigins[0].m_Origin[2] == 0);
+ CHECK(queueDescriptor.m_ViewOrigins[1].m_Origin[2] == 0);
+ CHECK(queueDescriptor.m_ViewOrigins[2].m_Origin[2] == 0);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+/// This function constructs a graph with both a splitter and a concat, and returns a pair of the workloads.
+template<typename SplitterWorkload, typename ConcatWorkload, armnn::DataType DataType>
+std::pair<std::unique_ptr<SplitterWorkload>, std::unique_ptr<ConcatWorkload>>
+ CreateSplitterConcatWorkloadTest(armnn::IWorkloadFactory &factory, armnn::Graph &graph)
+{
+ armnn::TensorInfo inputTensorInfo({ 1, 2, 100, 10 }, DataType);
+
+ armnn::TensorInfo splitTensorInfo1({ 1, 1, 100, 10 }, DataType);
+ armnn::TensorInfo splitTensorInfo2({ 1, 1, 100, 10 }, DataType);
+
+ //Constructs the graph.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+
+ armnn::ViewsDescriptor splitterViews(2);
+ splitterViews.SetViewOriginCoord(0, 0, 0);
+ splitterViews.SetViewOriginCoord(0, 1, 0);
+ splitterViews.SetViewOriginCoord(0, 2, 0);
+ splitterViews.SetViewOriginCoord(0, 3, 0);
+
+ splitterViews.SetViewOriginCoord(1, 0, 0);
+ splitterViews.SetViewOriginCoord(1, 1, 1);
+ splitterViews.SetViewOriginCoord(1, 2, 0);
+ splitterViews.SetViewOriginCoord(1, 3, 0);
+
+ // create splitter layer
+ Layer* const splitter = graph.AddLayer<SplitterLayer>(splitterViews, "splitter");
+ CHECK(splitter);
+
+ armnn::OriginsDescriptor concatViews(2);
+ concatViews.SetViewOriginCoord(0, 0, 0);
+ concatViews.SetViewOriginCoord(0, 1, 1);
+ concatViews.SetViewOriginCoord(0, 2, 0);
+ concatViews.SetViewOriginCoord(0, 3, 0);
+
+ concatViews.SetViewOriginCoord(1, 0, 0);
+ concatViews.SetViewOriginCoord(1, 1, 0);
+ concatViews.SetViewOriginCoord(1, 2, 0);
+ concatViews.SetViewOriginCoord(1, 3, 0);
+
+ // create concat layer
+ Layer* const concat = graph.AddLayer<ConcatLayer>(concatViews, "concat");
+ CHECK(concat);
+
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Adds connections.
+ // connect input to splitter
+ Connect(input, splitter, inputTensorInfo, 0, 0);
+ // connect splitter[0] to concat[1]
+ Connect(splitter, concat, splitTensorInfo1, 0, 1); // The splitter & concat are connected up.
+ // connect splitter[1] to concat[0]
+ Connect(splitter, concat, splitTensorInfo2, 1, 0); // So that the outputs are flipped round.
+ // connect concat to output
+ Connect(concat, output, inputTensorInfo, 0, 0);
+
+ // created tensor handles
+ CreateTensorHandles(graph, factory);
+
+ // created splitter workload
+ auto workloadSplitter = MakeAndCheckWorkload<SplitterWorkload>(*splitter, factory);
+ CHECK(workloadSplitter);
+ // created concat workload
+ auto workloadConcat = MakeAndCheckWorkload<ConcatWorkload>(*concat, factory);
+ CHECK(workloadConcat);
+
+ return {std::move(workloadSplitter), std::move(workloadConcat)};
+}
+
+
+/// This function constructs a graph with a splitter with two outputs. Each of the outputs is then
+/// connected to two different activation layers
+template<typename SplitterWorkload, typename ActivationWorkload, armnn::DataType DataType>
+void CreateSplitterMultipleInputsOneOutputWorkloadTest(armnn::IWorkloadFactory& factory, armnn::Graph& graph,
+ std::unique_ptr<SplitterWorkload>& wlSplitter,
+ std::unique_ptr<ActivationWorkload>& wlActiv0_0,
+ std::unique_ptr<ActivationWorkload>& wlActiv0_1,
+ std::unique_ptr<ActivationWorkload>& wlActiv1_0,
+ std::unique_ptr<ActivationWorkload>& wlActiv1_1)
+{
+ armnn::TensorInfo inputTensorInfo ({ 1, 3, 100, 50 }, DataType);
+ armnn::TensorInfo splitTensorInfo1({ 1, 1, 100, 50 }, DataType);
+ armnn::TensorInfo splitTensorInfo2({ 1, 2, 100, 50 }, DataType);
+
+ //Constructs the graph.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+
+ armnn::ViewsDescriptor splitterViews(2);
+
+ splitterViews.SetViewOriginCoord(0, 0, 0);
+ splitterViews.SetViewOriginCoord(0, 1, 0);
+ splitterViews.SetViewOriginCoord(0, 2, 0);
+ splitterViews.SetViewOriginCoord(0, 3, 0);
+
+ splitterViews.SetViewOriginCoord(1, 0, 0);
+ splitterViews.SetViewOriginCoord(1, 1, 1);
+ splitterViews.SetViewOriginCoord(1, 2, 0);
+ splitterViews.SetViewOriginCoord(1, 3, 0);
+
+ Layer* const splitter = graph.AddLayer<SplitterLayer>(splitterViews, "splitter");
+
+ armnn::ActivationDescriptor activationDesc;
+
+ Layer* const activ0_0 = graph.AddLayer<ActivationLayer>(activationDesc, "activ0_0");
+ Layer* const activ0_1 = graph.AddLayer<ActivationLayer>(activationDesc, "activ0_1");
+ Layer* const activ1_0 = graph.AddLayer<ActivationLayer>(activationDesc, "activ1_0");
+ Layer* const activ1_1 = graph.AddLayer<ActivationLayer>(activationDesc, "activ1_1");
+
+ Layer* const output1 = graph.AddLayer<OutputLayer>(1, "output1");
+ Layer* const output2 = graph.AddLayer<OutputLayer>(2, "output2");
+ Layer* const output3 = graph.AddLayer<OutputLayer>(3, "output3");
+ Layer* const output4 = graph.AddLayer<OutputLayer>(4, "output4");
+
+ // Adds connections.
+ Connect(input, splitter, inputTensorInfo, 0, 0);
+ Connect(splitter, activ0_0, splitTensorInfo1, 0, 0);
+ Connect(splitter, activ0_1, splitTensorInfo1, 0, 0);
+
+ Connect(splitter, activ1_0, splitTensorInfo2, 1, 0);
+ Connect(splitter, activ1_1, splitTensorInfo2, 1, 0);
+
+ Connect(activ0_0, output1, splitTensorInfo1, 0, 0);
+ Connect(activ0_1, output2, splitTensorInfo1, 0, 0);
+ Connect(activ1_0, output3, splitTensorInfo2, 0, 0);
+ Connect(activ1_1, output4, splitTensorInfo2, 0, 0);
+
+ CreateTensorHandles(graph, factory);
+
+ auto workloadSplitter = MakeAndCheckWorkload<SplitterWorkload>(*splitter, factory);
+ auto workloadActiv0_0 = MakeAndCheckWorkload<ActivationWorkload>(*activ0_0, factory);
+ auto workloadActiv0_1 = MakeAndCheckWorkload<ActivationWorkload>(*activ0_1, factory);
+ auto workloadActiv1_0 = MakeAndCheckWorkload<ActivationWorkload>(*activ1_0, factory);
+ auto workloadActiv1_1 = MakeAndCheckWorkload<ActivationWorkload>(*activ1_1, factory);
+
+ wlSplitter = std::move(workloadSplitter);
+ wlActiv0_0 = std::move(workloadActiv0_0);
+ wlActiv0_1 = std::move(workloadActiv0_1);
+ wlActiv1_0 = std::move(workloadActiv1_0);
+ wlActiv1_1 = std::move(workloadActiv1_1);
+}
+
+template <typename ResizeWorkload, armnn::DataType DataType>
+std::unique_ptr<ResizeWorkload> CreateResizeBilinearWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph,
+ DataLayout dataLayout = DataLayout::NCHW)
+{
+ TensorShape inputShape;
+ TensorShape outputShape;
+
+ switch (dataLayout) {
+ case DataLayout::NHWC:
+ inputShape = { 2, 4, 4, 3 };
+ outputShape = { 2, 2, 2, 3 };
+ break;
+ case DataLayout::NCHW:
+ default:
+ inputShape = { 2, 3, 4, 4 };
+ outputShape = { 2, 3, 2, 2 };
+ }
+
+ // Creates the layer we're testing.
+ ResizeDescriptor resizeDesc;
+ armnnUtils::DataLayoutIndexed dimensionIndices = dataLayout;
+ resizeDesc.m_Method = ResizeMethod::Bilinear;
+ resizeDesc.m_TargetWidth = outputShape[dimensionIndices.GetWidthIndex()];
+ resizeDesc.m_TargetHeight = outputShape[dimensionIndices.GetHeightIndex()];
+ resizeDesc.m_DataLayout = dataLayout;
+ Layer* const layer = graph.AddLayer<ResizeLayer>(resizeDesc, "resize");
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo inputTensorInfo(inputShape, DataType);
+ armnn::TensorInfo outputTensorInfo(outputShape, DataType);
+ Connect(input, layer, inputTensorInfo);
+ Connect(layer, output, outputTensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<ResizeWorkload>(*layer, factory);
+
+ auto queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+ CHECK(queueDescriptor.m_Parameters.m_DataLayout == dataLayout);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename BatchToSpaceNdWorkload, armnn::DataType DataType>
+std::unique_ptr<BatchToSpaceNdWorkload> CreateBatchToSpaceNdWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ BatchToSpaceNdDescriptor desc;
+ Layer* const layer = graph.AddLayer<BatchToSpaceNdLayer>(desc, "batchToSpace");
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo tensorInfo({1, 1, 1, 1}, DataType);
+
+ Connect(input, layer, tensorInfo);
+ Connect(layer, output, tensorInfo);
+
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<BatchToSpaceNdWorkload>(*layer, factory);
+
+ BatchToSpaceNdQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ return workload;
+}
+
+template <typename LogSoftmaxWorkload, armnn::DataType DataType>
+std::unique_ptr<LogSoftmaxWorkload> CreateLogSoftmaxWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ // Create the layer we're testing.
+ LogSoftmaxDescriptor logSoftmaxDescriptor;
+ // Set Axis to -1 if CL or Neon until further Axes are supported.
+ if (factory.GetBackendId() == armnn::Compute::CpuAcc || factory.GetBackendId() == armnn::Compute::GpuAcc)
+ {
+ logSoftmaxDescriptor.m_Axis = -1;
+ }
+
+ Layer* const layer = graph.AddLayer<LogSoftmaxLayer>(logSoftmaxDescriptor, "layer");
+ // Create extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connect up
+ armnn::TensorInfo tensorInfo({4, 1}, DataType);
+
+ Connect(input, layer, tensorInfo);
+ Connect(layer, output, tensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Make the workload and checks it.
+ auto workload = MakeAndCheckWorkload<LogSoftmaxWorkload>(*layer, factory);
+
+ LogSoftmaxQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Return so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename L2NormalizationWorkload, armnn::DataType DataType>
+std::unique_ptr<L2NormalizationWorkload> CreateL2NormalizationWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW)
+{
+ // Creates the layer we're testing.
+ L2NormalizationDescriptor layerDesc;
+ layerDesc.m_DataLayout = dataLayout;
+
+ Layer* const layer = graph.AddLayer<L2NormalizationLayer>(layerDesc, "l2norm");
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ TensorShape inputShape = (dataLayout == DataLayout::NCHW) ?
+ TensorShape{ 5, 20, 50, 67 } : TensorShape{ 5, 50, 67, 20 };
+ TensorShape outputShape = (dataLayout == DataLayout::NCHW) ?
+ TensorShape{ 5, 20, 50, 67 } : TensorShape{ 5, 50, 67, 20 };
+
+ // Connects up.
+ armnn::TensorInfo inputTensorInfo(inputShape, DataType);
+ armnn::TensorInfo outputTensorInfo(outputShape, DataType);
+ Connect(input, layer, inputTensorInfo);
+ Connect(layer, output, outputTensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<L2NormalizationWorkload>(*layer, factory);
+
+ L2NormalizationQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename ReshapeWorkload, armnn::DataType DataType>
+std::unique_ptr<ReshapeWorkload> CreateReshapeWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ // Creates the layer we're testing.
+ TensorShape outputShape({ 1, 4 });
+ ReshapeDescriptor reshapeDesc;
+ reshapeDesc.m_TargetShape = outputShape;
+ Layer* const layer = graph.AddLayer<ReshapeLayer>(reshapeDesc, "layer");
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo inputTensorInfo({ 4, 1 }, DataType);
+ armnn::TensorInfo outputTensorInfo(outputShape, DataType);
+ Connect(input, layer, inputTensorInfo);
+ Connect(layer, output, outputTensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<ReshapeWorkload>(*layer, factory);
+
+ ReshapeQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename ConvertFp16ToFp32Float32Workload>
+std::unique_ptr<ConvertFp16ToFp32Float32Workload> CreateConvertFp16ToFp32WorkloadTest(
+ armnn::IWorkloadFactory& factory, armnn::Graph& graph)
+{
+ // Creates the layer we're testing.
+ ConvertFp16ToFp32Layer* const layer = graph.AddLayer<ConvertFp16ToFp32Layer>("Fp16ToFp32Converter");
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo inputTensorInfo({1, 3, 2, 3}, armnn::DataType::Float16);
+ armnn::TensorInfo outputTensorInfo({1, 3, 2, 3}, armnn::DataType::Float32);
+ Connect(input, layer, inputTensorInfo);
+ Connect(layer, output, outputTensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<ConvertFp16ToFp32Float32Workload>(*layer, factory);
+
+ ConvertFp16ToFp32QueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename ConvertFp32ToFp16Float16Workload>
+std::unique_ptr<ConvertFp32ToFp16Float16Workload> CreateConvertFp32ToFp16WorkloadTest(
+ armnn::IWorkloadFactory& factory, armnn::Graph& graph)
+{
+ // Creates the layer we're testing.
+ ConvertFp32ToFp16Layer* const layer = graph.AddLayer<ConvertFp32ToFp16Layer>("Fp32ToFp16Converter");
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo inputTensorInfo({1, 3, 2, 3}, armnn::DataType::Float32);
+ armnn::TensorInfo outputTensorInfo({1, 3, 2, 3}, armnn::DataType::Float16);
+ Connect(input, layer, inputTensorInfo);
+ Connect(layer, output, outputTensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<ConvertFp32ToFp16Float16Workload>(*layer, factory);
+
+ ConvertFp32ToFp16QueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename MeanWorkload, armnn::DataType DataType>
+std::unique_ptr<MeanWorkload> CreateMeanWorkloadTest(armnn::IWorkloadFactory& factory, armnn::Graph& graph)
+{
+ // Reduce along the first and second dimensions, and do not keep the reduced dimensions.
+ MeanDescriptor descriptor({ 1, 2 }, false);
+
+ // Creates the layer we're testing.
+ Layer* const layer = graph.AddLayer<MeanLayer>(descriptor, "mean");
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo inputTensorInfo({ 1, 3, 7, 4 }, DataType);
+ armnn::TensorInfo outputTensorInfo({ 1, 4 }, DataType);
+ Connect(input, layer, inputTensorInfo);
+ Connect(layer, output, outputTensorInfo);
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<MeanWorkload>(*layer, factory);
+
+ MeanQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Parameters.m_Axis == descriptor.m_Axis);
+ CHECK(queueDescriptor.m_Parameters.m_KeepDims == descriptor.m_KeepDims);
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template<typename ConcatWorkload, armnn::DataType DataType>
+std::unique_ptr<ConcatWorkload> CreateConcatWorkloadTest(armnn::IWorkloadFactory &factory,
+ armnn::Graph &graph,
+ const armnn::TensorShape &outputShape,
+ unsigned int concatAxis)
+{
+ armnn::TensorInfo inputTensorInfo({ 2, 3, 2, 5 }, DataType);
+ armnn::TensorInfo outputTensorInfo(outputShape, DataType);
+
+ // Constructs the graph.
+ Layer* const input0 = graph.AddLayer<InputLayer>(0, "input0");
+ Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");
+ armnn::OriginsDescriptor descriptor;
+
+ std::vector<armnn::TensorShape> inputShapes{{ 2, 3, 2, 5 }, { 2, 3, 2, 5 }};
+
+ descriptor = CreateDescriptorForConcatenation(inputShapes.begin(),
+ inputShapes.end(),
+ concatAxis);
+
+ // create concat layer
+ Layer* const concat = graph.AddLayer<ConcatLayer>(descriptor, "concat");
+ CHECK(concat);
+
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Adds connections.
+ // connect input0 to concat
+ Connect(input0, concat, inputTensorInfo, 0, 0);
+ // connect input1 to concat
+ Connect(input1, concat, inputTensorInfo, 0, 1);
+ // connect concat to output
+ Connect(concat, output, outputTensorInfo, 0, 0);
+
+ // create tensor handles
+ CreateTensorHandles(graph, factory);
+
+ // create concat workload
+ auto workloadConcat = MakeAndCheckWorkload<ConcatWorkload>(*concat, factory);
+ CHECK(workloadConcat);
+
+ return workloadConcat;
+}
+
+template <typename PreCompiledWorkload, armnn::DataType dataType>
+std::pair<armnn::IOptimizedNetworkPtr, std::unique_ptr<PreCompiledWorkload>> CreatePreCompiledWorkloadTest(
+ armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph,
+ bool biasEnabled = false)
+{
+ IgnoreUnused(graph);
+
+ // build up the structure of the network
+ armnn::INetworkPtr net(armnn::INetwork::Create());
+
+ // Add an input layer
+ armnn::IConnectableLayer* const inputLayer = net->AddInputLayer(0, "input layer");
+ CHECK(inputLayer);
+
+ // ArmNN weights tensor shape is OIHW (out channels, in channels, height, width) for NCHW
+ // ArmNN weights tensor shape is OHWI (out channels, height, width, in channels) for NHWC
+ // this test is using NHWC, so the weights shape is OHWI
+ TensorInfo weightsTensorInfo(TensorShape({16, 1, 1, 16}), dataType, 0.9f, 0, true);
+ unsigned int weightsLength = weightsTensorInfo.GetNumElements();
+
+ using WeightType = armnn::ResolveType<dataType>;
+ std::vector<WeightType> convWeightsData(weightsLength);
+ for (unsigned int i = 0; i < weightsLength; ++i)
+ {
+ convWeightsData[i] = static_cast<WeightType>(i);
+ }
+
+ armnn::ConstTensor weights(weightsTensorInfo, convWeightsData);
+
+ // Add a layer that can be used in the PreCompiled layer
+ armnn::Convolution2dDescriptor convDesc2d;
+ convDesc2d.m_StrideX = 1;
+ convDesc2d.m_StrideY = 1;
+ convDesc2d.m_BiasEnabled = biasEnabled;
+ convDesc2d.m_DataLayout = armnn::DataLayout::NHWC;
+
+ armnn::IConnectableLayer* convLayer = nullptr;
+ const std::string convLayerName("conv layer");
+
+ if (biasEnabled)
+ {
+ constexpr armnn::DataType biasDataType = ( dataType == armnn::DataType::QAsymmU8) ?
+ armnn::DataType::Signed32 : armnn::DataType::Float32;
+
+ TensorInfo biasTensorInfo(TensorShape({16}), biasDataType, 0.9f * 0.9f, 0, true);
+ unsigned int biasLength = biasTensorInfo.GetNumElements();
+
+ using BiasType = armnn::ResolveType<biasDataType>;
+ std::vector<BiasType> biasData(biasLength);
+ std::fill(biasData.begin(), biasData.end(), static_cast<BiasType>(0));
+
+ armnn::ConstTensor biases(biasTensorInfo, biasData);
+
+ // Create convolution layer with biases
+ convLayer = net->AddConvolution2dLayer(convDesc2d,
+ weights,
+ Optional<ConstTensor>(biases),
+ convLayerName.c_str());
+ }
+ else
+ {
+ // Create convolution layer without biases
+ convLayer = net->AddConvolution2dLayer(convDesc2d,
+ weights,
+ EmptyOptional(),
+ convLayerName.c_str());
+ }
+
+ CHECK(convLayer);
+
+ // Add an output layer
+ armnn::IConnectableLayer* const outputLayer = net->AddOutputLayer(0, "output layer");
+ CHECK(outputLayer);
+
+ // set the tensors in the network (NHWC format)
+ TensorInfo inputTensorInfo(TensorShape({ 1, 16, 16, 16 }), dataType);
+ if (dataType == armnn::DataType::QAsymmU8)
+ {
+ inputTensorInfo.SetQuantizationOffset(0);
+ inputTensorInfo.SetQuantizationScale(0.9f);
+ }
+
+ TensorInfo outputTensorInfo(TensorShape({1, 16, 16, 16}), dataType);
+ if (dataType == armnn::DataType::QAsymmU8)
+ {
+ outputTensorInfo.SetQuantizationOffset(0);
+ outputTensorInfo.SetQuantizationScale(0.9f);
+ }
+
+ // Connect the layers
+ inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0));
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
+
+ convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+ convLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ // Optimize the network for the backend supported by the factory
+ std::vector<armnn::BackendId> backends = {factory.GetBackendId()};
+ armnn::IRuntime::CreationOptions options;
+ armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options));
+ armnn::OptimizerOptions optimizerOptions;
+ armnn::IOptimizedNetworkPtr optimizedNet = armnn::Optimize(*net, backends, runtime->GetDeviceSpec(),
+ optimizerOptions);
+ CHECK(optimizedNet != nullptr);
+
+ // Find the PreCompiled layer in the optimised graph
+ armnn::Graph& optimisedGraph = GetGraphForTesting(optimizedNet.get());
+ Layer* preCompiledLayer = nullptr;
+ for (auto& layer : optimisedGraph)
+ {
+ if (layer->GetType() == LayerType::PreCompiled)
+ {
+ preCompiledLayer = layer;
+ }
+ }
+ CHECK(preCompiledLayer != nullptr);
+
+ // Create the TensorHandles.
+ CreateTensorHandles(optimisedGraph, factory);
+
+ // Make the workload and check it.
+ auto workload = MakeAndCheckWorkload<PreCompiledWorkload>(*preCompiledLayer, factory);
+
+ PreCompiledQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns the workload so we can do extra, backend-specific tests.
+ // NOTE: We need to return the optimised network as well, otherwise it gets
+ // out of scope and the tensor handles get destructed
+ return std::make_pair(std::move(optimizedNet), std::move(workload));
+}
+
+template<typename ConstantWorkload, armnn::DataType DataType>
+std::unique_ptr<ConstantWorkload> CreateConstantWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph,
+ const armnn::TensorShape& outputShape)
+{
+ armnn::TensorInfo outputTensorInfo(outputShape, DataType);
+
+ // create constant layer
+ auto constant = graph.AddLayer<ConstantLayer>("constant");
+ CHECK(constant);
+ constant->m_LayerOutput = std::make_unique<ScopedTensorHandle>(outputTensorInfo);
+
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Adds connections.
+ // connect constant to output
+ Connect(constant, output, outputTensorInfo, 0, 0);
+
+ // create tensor handles
+ CreateTensorHandles(graph, factory);
+
+ // create Constant workload"
+ auto workloadConstant = MakeAndCheckWorkload<ConstantWorkload>(*constant, factory);
+ CHECK(workloadConstant);
+
+ return workloadConstant;
+}
+
+template <typename PreluWorkload>
+std::unique_ptr<PreluWorkload> CreatePreluWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph,
+ const armnn::TensorShape& inputShape,
+ const armnn::TensorShape& alphaShape,
+ const armnn::TensorShape& outputShape,
+ armnn::DataType dataType)
+{
+ // Creates the PReLU layer
+ Layer* const layer = graph.AddLayer<PreluLayer>("prelu");
+ CHECK(layer != nullptr);
+
+ // Creates extra layers
+ Layer* const input = graph.AddLayer<InputLayer> (0, "input");
+ Layer* const alpha = graph.AddLayer<InputLayer> (1, "alpha");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+ CHECK(input != nullptr);
+ CHECK(alpha != nullptr);
+ CHECK(output != nullptr);
+
+ // Connects up
+ armnn::TensorInfo inputTensorInfo (inputShape, dataType);
+ armnn::TensorInfo alphaTensorInfo (alphaShape, dataType);
+ armnn::TensorInfo outputTensorInfo(outputShape, dataType);
+ Connect(input, layer, inputTensorInfo, 0, 0);
+ Connect(alpha, layer, alphaTensorInfo, 0, 1);
+ Connect(layer, output, outputTensorInfo, 0, 0);
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it
+ auto workload = MakeAndCheckWorkload<PreluWorkload>(*layer, factory);
+
+ PreluQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 2);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ // Returns so we can do extra, backend-specific tests.
+ return workload;
+}
+
+template <typename SpaceToDepthWorkload, armnn::DataType DataType>
+std::unique_ptr<SpaceToDepthWorkload> CreateSpaceToDepthWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph)
+{
+ SpaceToDepthDescriptor desc;
+ desc.m_BlockSize = 2;
+ Layer* const layer = graph.AddLayer<SpaceToDepthLayer>(desc, "spaceToDepth");
+
+ // Creates extra layers.
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // Connects up.
+ armnn::TensorInfo inputTensorInfo({ 1, 2, 2, 1 }, DataType);
+ armnn::TensorInfo outputTensorInfo({ 1, 1, 1, 4 }, DataType);
+
+ Connect(input, layer, inputTensorInfo);
+ Connect(layer, output, outputTensorInfo);
+
+ CreateTensorHandles(graph, factory);
+
+ // Makes the workload and checks it.
+ auto workload = MakeAndCheckWorkload<SpaceToDepthWorkload>(*layer, factory);
+
+ SpaceToDepthQueueDescriptor queueDescriptor = workload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == 1);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ return workload;
+}
+
+template <typename StackWorkload, armnn::DataType DataType>
+std::unique_ptr<StackWorkload> CreateStackWorkloadTest(armnn::IWorkloadFactory& factory,
+ armnn::Graph& graph,
+ const armnn::TensorShape& inputShape,
+ const armnn::TensorShape& outputShape,
+ unsigned int axis,
+ unsigned int numInputs)
+{
+ armnn::TensorInfo inputTensorInfo(inputShape, DataType);
+ armnn::TensorInfo outputTensorInfo(outputShape, DataType);
+
+ // Constructs the Stack layer.
+ armnn::StackDescriptor descriptor(axis, numInputs, inputShape);
+ Layer* const stackLayer = graph.AddLayer<StackLayer>(descriptor, "stack");
+ CHECK(stackLayer != nullptr);
+
+ // Constructs layer inputs and output.
+ std::vector<Layer*> inputs;
+ for (unsigned int i=0; i<numInputs; ++i)
+ {
+ inputs.push_back(graph.AddLayer<InputLayer>(
+ static_cast<int>(i),
+ ("input" + std::to_string(i)).c_str()
+ ));
+ CHECK(inputs[i] != nullptr);
+ }
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+ CHECK(output != nullptr);
+
+ // Adds connections.
+ for (unsigned int i=0; i<numInputs; ++i)
+ {
+ Connect(inputs[i], stackLayer, inputTensorInfo, 0, i);
+ }
+ Connect(stackLayer, output, outputTensorInfo, 0, 0);
+
+ CreateTensorHandles(graph, factory);
+
+ auto stackWorkload = MakeAndCheckWorkload<StackWorkload>(*stackLayer, factory);
+ StackQueueDescriptor queueDescriptor = stackWorkload->GetData();
+ CHECK(queueDescriptor.m_Inputs.size() == numInputs);
+ CHECK(queueDescriptor.m_Outputs.size() == 1);
+
+ return stackWorkload;
+}
+
+} // Anonymous namespace
diff --git a/src/armnnTestUtils/DataTypeUtils.hpp b/src/armnnTestUtils/DataTypeUtils.hpp
new file mode 100644
index 0000000..528a573
--- /dev/null
+++ b/src/armnnTestUtils/DataTypeUtils.hpp
@@ -0,0 +1,45 @@
+//
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <ResolveType.hpp>
+
+
+#include <reference/workloads/Encoders.hpp>
+
+#include <vector>
+
+// Utility tenmplate to convert a collection of values to the correct type
+template <armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+std::vector<T> ConvertToDataType(const std::vector<float>& input,
+ const armnn::TensorInfo& inputTensorInfo)
+{
+ std::vector<T> output(input.size());
+ auto outputTensorInfo = inputTensorInfo;
+ outputTensorInfo.SetDataType(ArmnnType);
+
+ std::unique_ptr<armnn::Encoder<float>> pOutputEncoder = armnn::MakeEncoder<float>(outputTensorInfo, output.data());
+ armnn::Encoder<float>& rOutputEncoder = *pOutputEncoder;
+
+ for (auto it = input.begin(); it != input.end(); ++it)
+ {
+ rOutputEncoder.Set(*it);
+ ++rOutputEncoder;
+ }
+ return output;
+}
+
+// Utility tenmplate to convert a single value to the correct type
+template <typename T>
+T ConvertToDataType(const float& value,
+ const armnn::TensorInfo& tensorInfo)
+{
+ std::vector<T> output(1);
+ std::unique_ptr<armnn::Encoder<float>> pEncoder = armnn::MakeEncoder<float>(tensorInfo, output.data());
+ armnn::Encoder<float>& rEncoder = *pEncoder;
+ rEncoder.Set(value);
+ return output[0];
+}
diff --git a/src/armnn/test/GraphUtils.cpp b/src/armnnTestUtils/GraphUtils.cpp
similarity index 96%
rename from src/armnn/test/GraphUtils.cpp
rename to src/armnnTestUtils/GraphUtils.cpp
index bc6b562..15dc888 100644
--- a/src/armnn/test/GraphUtils.cpp
+++ b/src/armnnTestUtils/GraphUtils.cpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
diff --git a/src/armnnTestUtils/GraphUtils.hpp b/src/armnnTestUtils/GraphUtils.hpp
new file mode 100644
index 0000000..95f0704
--- /dev/null
+++ b/src/armnnTestUtils/GraphUtils.hpp
@@ -0,0 +1,25 @@
+//
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include <Graph.hpp>
+
+#include <string>
+
+
+bool GraphHasNamedLayer(const armnn::Graph& graph, const std::string& name);
+
+armnn::Layer* GetFirstLayerWithName(armnn::Graph& graph, const std::string& name);
+
+bool CheckNumberOfInputSlot(armnn::Layer* layer, unsigned int num);
+
+bool CheckNumberOfOutputSlot(armnn::Layer* layer, unsigned int num);
+
+bool IsConnected(armnn::Layer* srcLayer, armnn::Layer* destLayer,
+ unsigned int srcSlot, unsigned int destSlot,
+ const armnn::TensorInfo& expectedTensorInfo);
+
+bool CheckOrder(const armnn::Graph& graph, const armnn::Layer* first, const armnn::Layer* second);
+
diff --git a/src/backends/backendsCommon/test/TensorCopyUtils.cpp b/src/armnnTestUtils/TensorCopyUtils.cpp
similarity index 81%
rename from src/backends/backendsCommon/test/TensorCopyUtils.cpp
rename to src/armnnTestUtils/TensorCopyUtils.cpp
index ba7208c..14c6d5c 100644
--- a/src/backends/backendsCommon/test/TensorCopyUtils.cpp
+++ b/src/armnnTestUtils/TensorCopyUtils.cpp
@@ -1,9 +1,9 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#include "TensorCopyUtils.hpp"
+#include <armnnTestUtils/TensorCopyUtils.hpp>
#include <Half.hpp>
void CopyDataToITensorHandle(armnn::ITensorHandle* tensorHandle, const void* memory)
diff --git a/src/armnnTestUtils/TensorHelpers.hpp b/src/armnnTestUtils/TensorHelpers.hpp
new file mode 100644
index 0000000..d51e4b1
--- /dev/null
+++ b/src/armnnTestUtils/TensorHelpers.hpp
@@ -0,0 +1,235 @@
+//
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include <armnnTestUtils/PredicateResult.hpp>
+
+#include <armnn/Tensor.hpp>
+#include <armnn/utility/Assert.hpp>
+#include <armnnUtils/FloatingPointComparison.hpp>
+
+#include <QuantizeHelper.hpp>
+
+#include <doctest/doctest.h>
+
+#include <array>
+#include <cmath>
+#include <random>
+#include <vector>
+
+constexpr float g_FloatCloseToZeroTolerance = 1.0e-6f;
+
+template<typename T, bool isQuantized = true>
+struct SelectiveComparer
+{
+ static bool Compare(T a, T b)
+ {
+ return (std::max(a, b) - std::min(a, b)) <= 1;
+ }
+
+};
+
+template<typename T>
+struct SelectiveComparer<T, false>
+{
+ static bool Compare(T a, T b)
+ {
+ // If a or b is zero, percent_tolerance does an exact match, so compare to a small, constant tolerance instead.
+ if (a == 0.0f || b == 0.0f)
+ {
+ return std::abs(a - b) <= g_FloatCloseToZeroTolerance;
+ }
+
+ if (std::isinf(a) && a == b)
+ {
+ return true;
+ }
+
+ if (std::isnan(a) && std::isnan(b))
+ {
+ return true;
+ }
+
+ // For unquantized floats we use a tolerance of 1%.
+ return armnnUtils::within_percentage_tolerance(a, b);
+ }
+};
+
+template<typename T>
+bool SelectiveCompare(T a, T b)
+{
+ return SelectiveComparer<T, armnn::IsQuantizedType<T>()>::Compare(a, b);
+};
+
+template<typename T>
+bool SelectiveCompareBoolean(T a, T b)
+{
+ return (((a == 0) && (b == 0)) || ((a != 0) && (b != 0)));
+};
+
+template <typename T>
+armnn::PredicateResult CompareTensors(const std::vector<T>& actualData,
+ const std::vector<T>& expectedData,
+ const armnn::TensorShape& actualShape,
+ const armnn::TensorShape& expectedShape,
+ bool compareBoolean = false,
+ bool isDynamic = false)
+{
+ if (actualData.size() != expectedData.size())
+ {
+ armnn::PredicateResult res(false);
+ res.Message() << "Different data size ["
+ << actualData.size()
+ << "!="
+ << expectedData.size()
+ << "]";
+ return res;
+ }
+
+ if (actualShape.GetNumDimensions() != expectedShape.GetNumDimensions())
+ {
+ armnn::PredicateResult res(false);
+ res.Message() << "Different number of dimensions ["
+ << actualShape.GetNumDimensions()
+ << "!="
+ << expectedShape.GetNumDimensions()
+ << "]";
+ return res;
+ }
+
+ if (actualShape.GetNumElements() != expectedShape.GetNumElements())
+ {
+ armnn::PredicateResult res(false);
+ res.Message() << "Different number of elements ["
+ << actualShape.GetNumElements()
+ << "!="
+ << expectedShape.GetNumElements()
+ << "]";
+ return res;
+ }
+
+ unsigned int numberOfDimensions = actualShape.GetNumDimensions();
+
+ if (!isDynamic)
+ {
+ // Checks they are same shape.
+ for (unsigned int i = 0; i < numberOfDimensions; ++i)
+ {
+ if (actualShape[i] != expectedShape[i])
+ {
+ armnn::PredicateResult res(false);
+ res.Message() << "Different shapes ["
+ << actualShape[i]
+ << "!="
+ << expectedShape[i]
+ << "]";
+ return res;
+ }
+ }
+ }
+
+ // Fun iteration over n dimensions.
+ std::vector<unsigned int> indices;
+ for (unsigned int i = 0; i < numberOfDimensions; i++)
+ {
+ indices.emplace_back(0);
+ }
+
+ std::stringstream errorString;
+ int numFailedElements = 0;
+ constexpr int maxReportedDifferences = 3;
+ unsigned int index = 0;
+
+ // Compare data element by element.
+ while (true)
+ {
+ bool comparison;
+ // As true for uint8_t is non-zero (1-255) we must have a dedicated compare for Booleans.
+ if(compareBoolean)
+ {
+ comparison = SelectiveCompareBoolean(actualData[index], expectedData[index]);
+ }
+ else
+ {
+ comparison = SelectiveCompare(actualData[index], expectedData[index]);
+ }
+
+ if (!comparison)
+ {
+ ++numFailedElements;
+
+ if (numFailedElements <= maxReportedDifferences)
+ {
+ if (numFailedElements >= 2)
+ {
+ errorString << ", ";
+ }
+ errorString << "[";
+ for (unsigned int i = 0; i < numberOfDimensions; ++i)
+ {
+ errorString << indices[i];
+ if (i != numberOfDimensions - 1)
+ {
+ errorString << ",";
+ }
+ }
+ errorString << "]";
+
+ errorString << " (" << +actualData[index] << " != " << +expectedData[index] << ")";
+ }
+ }
+
+ ++indices[numberOfDimensions - 1];
+ for (unsigned int i=numberOfDimensions-1; i>0; i--)
+ {
+ if (indices[i] == actualShape[i])
+ {
+ indices[i] = 0;
+ ++indices[i - 1];
+ }
+ }
+ if (indices[0] == actualShape[0])
+ {
+ break;
+ }
+
+ index++;
+ }
+
+ armnn::PredicateResult comparisonResult(true);
+ if (numFailedElements > 0)
+ {
+ comparisonResult.SetResult(false);
+ comparisonResult.Message() << numFailedElements << " different values at: ";
+ if (numFailedElements > maxReportedDifferences)
+ {
+ errorString << ", ... (and " << (numFailedElements - maxReportedDifferences) << " other differences)";
+ }
+ comparisonResult.Message() << errorString.str();
+ }
+
+ return comparisonResult;
+}
+
+template <typename T>
+std::vector<T> MakeRandomTensor(const armnn::TensorInfo& tensorInfo,
+ unsigned int seed,
+ float min = -10.0f,
+ float max = 10.0f)
+{
+ std::mt19937 gen(seed);
+ std::uniform_real_distribution<float> dist(min, max);
+
+ std::vector<float> init(tensorInfo.GetNumElements());
+ for (unsigned int i = 0; i < init.size(); i++)
+ {
+ init[i] = dist(gen);
+ }
+
+ const float qScale = tensorInfo.GetQuantizationScale();
+ const int32_t qOffset = tensorInfo.GetQuantizationOffset();
+
+ return armnnUtils::QuantizedVector<T>(init, qScale, qOffset);
+}
diff --git a/src/armnn/test/TestUtils.cpp b/src/armnnTestUtils/TestUtils.cpp
similarity index 95%
rename from src/armnn/test/TestUtils.cpp
rename to src/armnnTestUtils/TestUtils.cpp
index 97cc80c..9ac0b39 100644
--- a/src/armnn/test/TestUtils.cpp
+++ b/src/armnnTestUtils/TestUtils.cpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
diff --git a/src/armnnTestUtils/TestUtils.hpp b/src/armnnTestUtils/TestUtils.hpp
new file mode 100644
index 0000000..d5b6d1b
--- /dev/null
+++ b/src/armnnTestUtils/TestUtils.hpp
@@ -0,0 +1,58 @@
+//
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <armnn/INetwork.hpp>
+#include <Graph.hpp>
+#include <Runtime.hpp>
+
+void Connect(armnn::IConnectableLayer* from, armnn::IConnectableLayer* to, const armnn::TensorInfo& tensorInfo,
+ unsigned int fromIndex = 0, unsigned int toIndex = 0);
+
+template <typename LayerT>
+bool IsLayerOfType(const armnn::Layer* const layer)
+{
+ return (layer->GetType() == armnn::LayerEnumOf<LayerT>());
+}
+
+inline bool CheckSequence(const armnn::Graph::ConstIterator first, const armnn::Graph::ConstIterator last)
+{
+ return (first == last);
+}
+
+/// Checks each unary function in Us evaluates true for each correspondent layer in the sequence [first, last).
+template <typename U, typename... Us>
+bool CheckSequence(const armnn::Graph::ConstIterator first, const armnn::Graph::ConstIterator last, U&& u, Us&&... us)
+{
+ return u(*first) && CheckSequence(std::next(first), last, us...);
+}
+
+template <typename LayerT>
+bool CheckRelatedLayers(armnn::Graph& graph, const std::list<std::string>& testRelatedLayers)
+{
+ for (auto& layer : graph)
+ {
+ if (layer->GetType() == armnn::LayerEnumOf<LayerT>())
+ {
+ auto& relatedLayers = layer->GetRelatedLayerNames();
+ if (!std::equal(relatedLayers.begin(), relatedLayers.end(), testRelatedLayers.begin(),
+ testRelatedLayers.end()))
+ {
+ return false;
+ }
+ }
+ }
+
+ return true;
+}
+
+namespace armnn
+{
+Graph& GetGraphForTesting(IOptimizedNetwork* optNetPtr);
+ModelOptions& GetModelOptionsForTesting(IOptimizedNetwork* optNetPtr);
+profiling::ProfilingService& GetProfilingService(RuntimeImpl* runtime);
+
+} // namespace armnn
\ No newline at end of file
diff --git a/src/armnn/test/UnitTests.cpp b/src/armnnTestUtils/UnitTests.cpp
similarity index 100%
rename from src/armnn/test/UnitTests.cpp
rename to src/armnnTestUtils/UnitTests.cpp
diff --git a/src/armnnTestUtils/UnitTests.hpp b/src/armnnTestUtils/UnitTests.hpp
new file mode 100644
index 0000000..788ad87
--- /dev/null
+++ b/src/armnnTestUtils/UnitTests.hpp
@@ -0,0 +1,191 @@
+//
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "TensorHelpers.hpp"
+#include "WorkloadTestUtils.hpp"
+
+#include <armnn/Logging.hpp>
+#include <armnn/Utils.hpp>
+#include <reference/RefWorkloadFactory.hpp>
+#include <reference/test/RefWorkloadFactoryHelper.hpp>
+
+#include <backendsCommon/test/WorkloadFactoryHelper.hpp>
+
+#include <armnnTestUtils/LayerTestResult.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+
+#include <doctest/doctest.h>
+
+inline void ConfigureLoggingTest()
+{
+ // Configures logging for both the ARMNN library and this test program.
+ armnn::ConfigureLogging(true, true, armnn::LogSeverity::Fatal);
+}
+
+// The following macros require the caller to have defined FactoryType, with one of the following using statements:
+//
+// using FactoryType = armnn::RefWorkloadFactory;
+// using FactoryType = armnn::ClWorkloadFactory;
+// using FactoryType = armnn::NeonWorkloadFactory;
+
+/// Executes CHECK_MESSAGE on CompareTensors() return value so that the predicate_result message is reported.
+/// If the test reports itself as not supported then the tensors are not compared.
+/// Additionally this checks that the supportedness reported by the test matches the name of the test.
+/// Unsupported tests must be 'tagged' by including "UNSUPPORTED" in their name.
+/// This is useful because it clarifies that the feature being tested is not actually supported
+/// (a passed test with the name of a feature would imply that feature was supported).
+/// If support is added for a feature, the test case will fail because the name incorrectly contains UNSUPPORTED.
+/// If support is removed for a feature, the test case will fail because the name doesn't contain UNSUPPORTED.
+template <typename T, std::size_t n>
+void CompareTestResultIfSupported(const std::string& testName, const LayerTestResult<T, n>& testResult)
+{
+ bool testNameIndicatesUnsupported = testName.find("UNSUPPORTED") != std::string::npos;
+ CHECK_MESSAGE(testNameIndicatesUnsupported != testResult.m_Supported,
+ "The test name does not match the supportedness it is reporting");
+ if (testResult.m_Supported)
+ {
+ auto result = CompareTensors(testResult.m_ActualData,
+ testResult.m_ExpectedData,
+ testResult.m_ActualShape,
+ testResult.m_ExpectedShape,
+ testResult.m_CompareBoolean);
+ CHECK_MESSAGE(result.m_Result, result.m_Message.str());
+ }
+}
+
+template <typename T, std::size_t n>
+void CompareTestResultIfSupported(const std::string& testName, const std::vector<LayerTestResult<T, n>>& testResult)
+{
+ bool testNameIndicatesUnsupported = testName.find("UNSUPPORTED") != std::string::npos;
+ for (unsigned int i = 0; i < testResult.size(); ++i)
+ {
+ CHECK_MESSAGE(testNameIndicatesUnsupported != testResult[i].m_Supported,
+ "The test name does not match the supportedness it is reporting");
+ if (testResult[i].m_Supported)
+ {
+ auto result = CompareTensors(testResult[i].m_ActualData,
+ testResult[i].m_ExpectedData,
+ testResult[i].m_ActualShape,
+ testResult[i].m_ExpectedShape);
+ CHECK_MESSAGE(result.m_Result, result.m_Message.str());
+ }
+ }
+}
+
+template<typename FactoryType, typename TFuncPtr, typename... Args>
+void RunTestFunction(const char* testName, TFuncPtr testFunction, Args... args)
+{
+ std::unique_ptr<armnn::IProfiler> profiler = std::make_unique<armnn::IProfiler>();
+ armnn::ProfilerManager::GetInstance().RegisterProfiler(profiler.get());
+
+ auto memoryManager = WorkloadFactoryHelper<FactoryType>::GetMemoryManager();
+ FactoryType workloadFactory = WorkloadFactoryHelper<FactoryType>::GetFactory(memoryManager);
+
+ auto testResult = (*testFunction)(workloadFactory, memoryManager, args...);
+ CompareTestResultIfSupported(testName, testResult);
+
+ armnn::ProfilerManager::GetInstance().RegisterProfiler(nullptr);
+}
+
+
+template<typename FactoryType, typename TFuncPtr, typename... Args>
+void RunTestFunctionUsingTensorHandleFactory(const char* testName, TFuncPtr testFunction, Args... args)
+{
+ std::unique_ptr<armnn::IProfiler> profiler = std::make_unique<armnn::IProfiler>();
+ armnn::ProfilerManager::GetInstance().RegisterProfiler(profiler.get());
+
+ auto memoryManager = WorkloadFactoryHelper<FactoryType>::GetMemoryManager();
+ FactoryType workloadFactory = WorkloadFactoryHelper<FactoryType>::GetFactory(memoryManager);
+
+ auto tensorHandleFactory = WorkloadFactoryHelper<FactoryType>::GetTensorHandleFactory(memoryManager);
+
+ auto testResult = (*testFunction)(workloadFactory, memoryManager, tensorHandleFactory, args...);
+ CompareTestResultIfSupported(testName, testResult);
+
+ armnn::ProfilerManager::GetInstance().RegisterProfiler(nullptr);
+}
+
+#define ARMNN_SIMPLE_TEST_CASE(TestName, TestFunction) \
+ TEST_CASE(#TestName) \
+ { \
+ TestFunction(); \
+ }
+
+#define ARMNN_AUTO_TEST_CASE(TestName, TestFunction, ...) \
+ TEST_CASE(#TestName) \
+ { \
+ RunTestFunction<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
+ }
+
+#define ARMNN_AUTO_TEST_FIXTURE(TestName, Fixture, TestFunction, ...) \
+ TEST_CASE_FIXTURE(Fixture, #TestName) \
+ { \
+ RunTestFunction<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
+ }
+
+#define ARMNN_AUTO_TEST_CASE_WITH_THF(TestName, TestFunction, ...) \
+ TEST_CASE(#TestName) \
+ { \
+ RunTestFunctionUsingTensorHandleFactory<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
+ }
+
+#define ARMNN_AUTO_TEST_FIXTURE_WITH_THF(TestName, Fixture, TestFunction, ...) \
+ TEST_CASE_FIXTURE(Fixture, #TestName) \
+ { \
+ RunTestFunctionUsingTensorHandleFactory<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
+ }
+
+template<typename FactoryType, typename TFuncPtr, typename... Args>
+void CompareRefTestFunction(const char* testName, TFuncPtr testFunction, Args... args)
+{
+ auto memoryManager = WorkloadFactoryHelper<FactoryType>::GetMemoryManager();
+ FactoryType workloadFactory = WorkloadFactoryHelper<FactoryType>::GetFactory(memoryManager);
+
+ armnn::RefWorkloadFactory refWorkloadFactory;
+
+ auto testResult = (*testFunction)(workloadFactory, memoryManager, refWorkloadFactory, args...);
+ CompareTestResultIfSupported(testName, testResult);
+}
+
+template<typename FactoryType, typename TFuncPtr, typename... Args>
+void CompareRefTestFunctionUsingTensorHandleFactory(const char* testName, TFuncPtr testFunction, Args... args)
+{
+ auto memoryManager = WorkloadFactoryHelper<FactoryType>::GetMemoryManager();
+ FactoryType workloadFactory = WorkloadFactoryHelper<FactoryType>::GetFactory(memoryManager);
+
+ armnn::RefWorkloadFactory refWorkloadFactory;
+ auto tensorHandleFactory = WorkloadFactoryHelper<FactoryType>::GetTensorHandleFactory(memoryManager);
+ auto refTensorHandleFactory =
+ RefWorkloadFactoryHelper::GetTensorHandleFactory(memoryManager);
+
+ auto testResult = (*testFunction)(
+ workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, args...);
+ CompareTestResultIfSupported(testName, testResult);
+}
+
+#define ARMNN_COMPARE_REF_AUTO_TEST_CASE(TestName, TestFunction, ...) \
+ TEST_CASE(#TestName) \
+ { \
+ CompareRefTestFunction<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
+ }
+
+#define ARMNN_COMPARE_REF_AUTO_TEST_CASE_WITH_THF(TestName, TestFunction, ...) \
+ TEST_CASE(#TestName) \
+ { \
+ CompareRefTestFunctionUsingTensorHandleFactory<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
+ }
+
+#define ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(TestName, Fixture, TestFunction, ...) \
+ TEST_CASE_FIXTURE(Fixture, #TestName) \
+ { \
+ CompareRefTestFunction<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
+ }
+
+#define ARMNN_COMPARE_REF_FIXTURE_TEST_CASE_WITH_THF(TestName, Fixture, TestFunction, ...) \
+ TEST_CASE_FIXTURE(Fixture, #TestName) \
+ { \
+ CompareRefTestFunctionUsingTensorHandleFactory<FactoryType>(#TestName, &TestFunction, ##__VA_ARGS__); \
+ }
diff --git a/src/armnnTestUtils/WorkloadTestUtils.hpp b/src/armnnTestUtils/WorkloadTestUtils.hpp
new file mode 100644
index 0000000..856e54a
--- /dev/null
+++ b/src/armnnTestUtils/WorkloadTestUtils.hpp
@@ -0,0 +1,113 @@
+//
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include <armnn/Tensor.hpp>
+
+#include <armnn/backends/IBackendInternal.hpp>
+#include <armnn/backends/IMemoryManager.hpp>
+#include <backendsCommon/Workload.hpp>
+#include <backendsCommon/WorkloadInfo.hpp>
+
+namespace armnn
+{
+class ITensorHandle;
+} // namespace armnn
+
+namespace
+{
+
+template <typename QueueDescriptor>
+void AddInputToWorkload(QueueDescriptor& descriptor,
+ armnn::WorkloadInfo& info,
+ const armnn::TensorInfo& tensorInfo,
+ armnn::ITensorHandle* tensorHandle)
+{
+ descriptor.m_Inputs.push_back(tensorHandle);
+ info.m_InputTensorInfos.push_back(tensorInfo);
+}
+
+template <typename QueueDescriptor>
+void AddOutputToWorkload(QueueDescriptor& descriptor,
+ armnn::WorkloadInfo& info,
+ const armnn::TensorInfo& tensorInfo,
+ armnn::ITensorHandle* tensorHandle)
+{
+ descriptor.m_Outputs.push_back(tensorHandle);
+ info.m_OutputTensorInfos.push_back(tensorInfo);
+}
+
+template <typename QueueDescriptor>
+void SetWorkloadInput(QueueDescriptor& descriptor,
+ armnn::WorkloadInfo& info,
+ unsigned int index,
+ const armnn::TensorInfo& tensorInfo,
+ armnn::ITensorHandle* tensorHandle)
+{
+ descriptor.m_Inputs[index] = tensorHandle;
+ info.m_InputTensorInfos[index] = tensorInfo;
+}
+
+template <typename QueueDescriptor>
+void SetWorkloadOutput(QueueDescriptor& descriptor,
+ armnn::WorkloadInfo& info,
+ unsigned int index,
+ const armnn::TensorInfo& tensorInfo,
+ armnn::ITensorHandle* tensorHandle)
+{
+ descriptor.m_Outputs[index] = tensorHandle;
+ info.m_OutputTensorInfos[index] = tensorInfo;
+}
+
+inline void ExecuteWorkload(armnn::IWorkload& workload,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ bool memoryManagementRequested = true)
+{
+ const bool manageMemory = memoryManager && memoryManagementRequested;
+
+ // Acquire working memory (if needed)
+ if (manageMemory)
+ {
+ memoryManager->Acquire();
+ }
+
+ // Perform PostAllocationConfiguration
+ workload.PostAllocationConfigure();
+
+ // Execute the workload
+ workload.Execute();
+
+ // Release working memory (if needed)
+ if (manageMemory)
+ {
+ memoryManager->Release();
+ }
+}
+
+inline armnn::Optional<armnn::DataType> GetBiasTypeFromWeightsType(armnn::Optional<armnn::DataType> weightsType)
+{
+ if (!weightsType)
+ {
+ return weightsType;
+ }
+
+ switch(weightsType.value())
+ {
+ case armnn::DataType::BFloat16:
+ case armnn::DataType::Float16:
+ case armnn::DataType::Float32:
+ return weightsType;
+ case armnn::DataType::QAsymmS8:
+ case armnn::DataType::QAsymmU8:
+ case armnn::DataType::QSymmS8:
+ case armnn::DataType::QSymmS16:
+ return armnn::DataType::Signed32;
+ default:
+ ARMNN_ASSERT_MSG(false, "GetBiasTypeFromWeightsType(): Unsupported data type.");
+ }
+ return armnn::EmptyOptional();
+}
+
+} // anonymous namespace
diff --git a/src/armnnTfLiteParser/test/DetectionPostProcess.cpp b/src/armnnTfLiteParser/test/DetectionPostProcess.cpp
index 4000d49..5dc78c6 100644
--- a/src/armnnTfLiteParser/test/DetectionPostProcess.cpp
+++ b/src/armnnTfLiteParser/test/DetectionPostProcess.cpp
@@ -6,7 +6,7 @@
#include "ParserFlatbuffersFixture.hpp"
#include "ParserPrototxtFixture.hpp"
#include "ParserHelper.hpp"
-#include "test/GraphUtils.hpp"
+#include <GraphUtils.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <QuantizeHelper.hpp>
diff --git a/src/armnnTfLiteParser/test/ParserFlatbuffersFixture.hpp b/src/armnnTfLiteParser/test/ParserFlatbuffersFixture.hpp
index 871f647..6b35558 100644
--- a/src/armnnTfLiteParser/test/ParserFlatbuffersFixture.hpp
+++ b/src/armnnTfLiteParser/test/ParserFlatbuffersFixture.hpp
@@ -17,7 +17,7 @@
#include <ResolveType.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <fmt/format.h>
#include <doctest/doctest.h>
diff --git a/src/armnnUtils/ParserPrototxtFixture.hpp b/src/armnnUtils/ParserPrototxtFixture.hpp
index 76e65df..31ee829 100644
--- a/src/armnnUtils/ParserPrototxtFixture.hpp
+++ b/src/armnnUtils/ParserPrototxtFixture.hpp
@@ -6,7 +6,7 @@
#pragma once
#include <armnn/IRuntime.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <Network.hpp>
#include <VerificationHelpers.hpp>
diff --git a/src/backends/aclCommon/test/CMakeLists.txt b/src/backends/aclCommon/test/CMakeLists.txt
index 756ef4a..7eb232a 100644
--- a/src/backends/aclCommon/test/CMakeLists.txt
+++ b/src/backends/aclCommon/test/CMakeLists.txt
@@ -13,6 +13,7 @@
add_library(armnnAclCommonUnitTests OBJECT ${armnnAclCommonUnitTests_sources})
target_include_directories(armnnAclCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnn)
target_include_directories(armnnAclCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnnUtils)
+target_include_directories(armnnAclCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnnTestUtils)
target_include_directories(armnnAclCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/backends)
target_include_directories(armnnAclCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/profiling)
target_include_directories(armnnAclCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/profiling/common/include)
diff --git a/src/backends/aclCommon/test/CreateWorkloadClNeon.hpp b/src/backends/aclCommon/test/CreateWorkloadClNeon.hpp
index bdae998..6a0d5cf 100644
--- a/src/backends/aclCommon/test/CreateWorkloadClNeon.hpp
+++ b/src/backends/aclCommon/test/CreateWorkloadClNeon.hpp
@@ -4,8 +4,8 @@
//
#pragma once
-#include <test/CreateWorkload.hpp>
-#include <test/PredicateResult.hpp>
+#include <CreateWorkload.hpp>
+#include <armnnTestUtils/PredicateResult.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <backendsCommon/MemCopyWorkload.hpp>
#include <reference/RefWorkloadFactory.hpp>
diff --git a/src/backends/aclCommon/test/MemCopyTestImpl.hpp b/src/backends/aclCommon/test/MemCopyTestImpl.hpp
index 91ba4ea..d943cfd 100644
--- a/src/backends/aclCommon/test/MemCopyTestImpl.hpp
+++ b/src/backends/aclCommon/test/MemCopyTestImpl.hpp
@@ -5,15 +5,14 @@
#pragma once
#include <ResolveType.hpp>
-
#include <armnn/backends/IBackendInternal.hpp>
-#include <backendsCommon/test/LayerTests.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadFactoryHelper.hpp>
+#include <test/TensorHelpers.hpp>
#include <backendsCommon/test/WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <armnnTestUtils/LayerTestResult.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <backendsCommon/test/WorkloadFactoryHelper.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/WorkloadFactory.cpp b/src/backends/backendsCommon/WorkloadFactory.cpp
index ef2a348..93932a8 100644
--- a/src/backends/backendsCommon/WorkloadFactory.cpp
+++ b/src/backends/backendsCommon/WorkloadFactory.cpp
@@ -8,6 +8,7 @@
#include <armnn/Types.hpp>
#include <armnn/LayerSupport.hpp>
+#include <armnn/backends/IBackendInternal.hpp>
#include <armnn/backends/ILayerSupport.hpp>
#include <armnn/BackendHelper.hpp>
#include <armnn/BackendRegistry.hpp>
@@ -17,7 +18,7 @@
#include <backendsCommon/WorkloadFactory.hpp>
#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+//#include <WorkloadTestUtils.hpp>
#include <sstream>
@@ -45,6 +46,31 @@
} // anonymous namespace
+inline armnn::Optional<armnn::DataType> GetBiasTypeFromWeightsType(armnn::Optional<armnn::DataType> weightsType)
+{
+ if (!weightsType)
+ {
+ return weightsType;
+ }
+
+ switch(weightsType.value())
+ {
+ case armnn::DataType::BFloat16:
+ case armnn::DataType::Float16:
+ case armnn::DataType::Float32:
+ return weightsType;
+ case armnn::DataType::QAsymmS8:
+ case armnn::DataType::QAsymmU8:
+ case armnn::DataType::QSymmS8:
+ case armnn::DataType::QSymmS16:
+ return armnn::DataType::Signed32;
+ default:
+ ARMNN_ASSERT_MSG(false, "GetBiasTypeFromWeightsType(): Unsupported data type.");
+ }
+ return armnn::EmptyOptional();
+}
+
+
bool IWorkloadFactory::IsLayerConfigurationSupported(const BackendId& backendId,
const IConnectableLayer& connectableLayer,
Optional<DataType> dataType,
diff --git a/src/backends/backendsCommon/common.mk b/src/backends/backendsCommon/common.mk
index 206faf5..8f97669 100644
--- a/src/backends/backendsCommon/common.mk
+++ b/src/backends/backendsCommon/common.mk
@@ -35,7 +35,6 @@
# up by the Android.mk file in the root of ArmNN
COMMON_TEST_SOURCES := \
- test/CommonTestUtils.cpp \
test/CustomMemoryOptimizerStrategyTests.cpp \
test/InstanceNormalizationEndToEndTestImpl.cpp \
test/JsonPrinterTestImpl.cpp \
@@ -43,7 +42,6 @@
test/QLstmEndToEndTestImpl.cpp \
test/QuantizedLstmEndToEndTestImpl.cpp \
test/SpaceToDepthEndToEndTestImpl.cpp \
- test/TensorCopyUtils.cpp \
test/layerTests/AbsTestImpl.cpp \
test/layerTests/ActivationTestImpl.cpp \
test/layerTests/AdditionTestImpl.cpp \
diff --git a/src/backends/backendsCommon/test/ActivationEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ActivationEndToEndTestImpl.hpp
index f7d4596..10e8363 100644
--- a/src/backends/backendsCommon/test/ActivationEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/ActivationEndToEndTestImpl.hpp
@@ -8,7 +8,9 @@
#include <armnn/INetwork.hpp>
#include <armnn/TypesUtils.hpp>
-#include <backendsCommon/test/CommonTestUtils.hpp>
+
+#include <CommonTestUtils.hpp>
+
#include <ResolveType.hpp>
namespace
diff --git a/src/backends/backendsCommon/test/ActivationFixture.hpp b/src/backends/backendsCommon/test/ActivationFixture.hpp
index c61f3f0..caa67ac 100644
--- a/src/backends/backendsCommon/test/ActivationFixture.hpp
+++ b/src/backends/backendsCommon/test/ActivationFixture.hpp
@@ -4,12 +4,12 @@
//
#pragma once
-#include "TensorCopyUtils.hpp"
-#include "WorkloadTestUtils.hpp"
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
#include <armnn/utility/NumericCast.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
struct ActivationFixture
{
diff --git a/src/backends/backendsCommon/test/ArgMinMaxEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ArgMinMaxEndToEndTestImpl.hpp
index 041f9f8..1b65385 100644
--- a/src/backends/backendsCommon/test/ArgMinMaxEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/ArgMinMaxEndToEndTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <QuantizeHelper.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/BackendProfilingTests.cpp b/src/backends/backendsCommon/test/BackendProfilingTests.cpp
index 62c06fe..b40964c 100644
--- a/src/backends/backendsCommon/test/BackendProfilingTests.cpp
+++ b/src/backends/backendsCommon/test/BackendProfilingTests.cpp
@@ -14,7 +14,7 @@
#include "ProfilingUtils.hpp"
#include "RequestCounterDirectoryCommandHandler.hpp"
-#include <test/TestUtils.hpp>
+#include <TestUtils.hpp>
#include <armnn/utility/IgnoreUnused.hpp>
#include <armnn/BackendId.hpp>
diff --git a/src/backends/backendsCommon/test/BatchToSpaceNdEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/BatchToSpaceNdEndToEndTestImpl.hpp
index 859694c..87fccd8 100644
--- a/src/backends/backendsCommon/test/BatchToSpaceNdEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/BatchToSpaceNdEndToEndTestImpl.hpp
@@ -8,7 +8,7 @@
#include <armnn/INetwork.hpp>
-#include <backendsCommon/test/CommonTestUtils.hpp>
+#include <CommonTestUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/CMakeLists.txt b/src/backends/backendsCommon/test/CMakeLists.txt
index 958f484..bb85f7e 100644
--- a/src/backends/backendsCommon/test/CMakeLists.txt
+++ b/src/backends/backendsCommon/test/CMakeLists.txt
@@ -10,12 +10,15 @@
BackendIdTests.cpp
BackendProfilingTests.cpp
BackendRegistryTests.cpp
+ CommonTestUtils.hpp
ChannelShuffleEndToEndTestImpl.hpp
ComparisonEndToEndTestImpl.hpp
CompatibilityTests.cpp
ConcatEndToEndTestImpl.hpp
Convolution3dEndToEndTestImpl.hpp
CustomMemoryOptimizerStrategyTests.cpp
+ DataLayoutUtils.hpp
+ DataTypeUtils.hpp
DefaultAsyncExecuteTest.cpp
DepthToSpaceEndToEndTestImpl.hpp
DequantizeEndToEndTestImpl.hpp
@@ -54,7 +57,9 @@
SpaceToDepthEndToEndTestImpl.hpp
SplitterEndToEndTestImpl.hpp
StridedSliceAsyncEndToEndTest.hpp
+ TensorCopyUtils.hpp
WorkloadFactoryHelper.hpp
+ WorkloadTestUtils.hpp
layerTests/AbsTestImpl.cpp
layerTests/AbsTestImpl.hpp
layerTests/ActivationTestImpl.cpp
@@ -116,6 +121,7 @@
layerTests/InstanceNormalizationTestImpl.hpp
layerTests/L2NormalizationTestImpl.cpp
layerTests/L2NormalizationTestImpl.hpp
+ layerTests/LayerTestResult.hpp
layerTests/LogTestImpl.cpp
layerTests/LogTestImpl.hpp
layerTests/LogicalTestImpl.cpp
@@ -200,6 +206,7 @@
add_library(armnnBackendsCommonUnitTests OBJECT ${armnnBackendsCommonUnitTests_sources})
target_include_directories(armnnBackendsCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnn)
target_include_directories(armnnBackendsCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnnUtils)
+target_include_directories(armnnBackendsCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnnTestUtils)
target_include_directories(armnnBackendsCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/backends)
target_include_directories(armnnBackendsCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/profiling)
target_include_directories(armnnBackendsCommonUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/profiling/common/include)
diff --git a/src/backends/backendsCommon/test/ChannelShuffleEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ChannelShuffleEndToEndTestImpl.hpp
index 7d46be7..27907f1 100644
--- a/src/backends/backendsCommon/test/ChannelShuffleEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/ChannelShuffleEndToEndTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <armnn/INetwork.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/CommonTestUtils.hpp b/src/backends/backendsCommon/test/CommonTestUtils.hpp
index 07523d7..72e3860 100644
--- a/src/backends/backendsCommon/test/CommonTestUtils.hpp
+++ b/src/backends/backendsCommon/test/CommonTestUtils.hpp
@@ -1,119 +1,12 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
+// This file is deprecated and will be removed soon.
+// Please use the new header in armnnTestUtils instead.
+// This will use the new armnnTestUtils header.
+#include "../../../armnnTestUtils/CommonTestUtils.hpp"
-#include <Graph.hpp>
-#include <SubgraphView.hpp>
-#include <SubgraphViewSelector.hpp>
-#include <ResolveType.hpp>
-
-#include <armnn/BackendRegistry.hpp>
-
-#include <armnn/Types.hpp>
-#include <backendsCommon/TensorHandle.hpp>
-
-#include <test/TestUtils.hpp>
-
-#include <algorithm>
-#include <random>
-#include <vector>
-
-// Checks that two collections have the exact same contents (in any order)
-// The given collections do not have to contain duplicates
-// Cannot use std::sort here because std lists have their own std::list::sort method
-template <typename CollectionType>
-bool AreEqual(const CollectionType& lhs, const CollectionType& rhs)
-{
- if (lhs.size() != rhs.size())
- {
- return false;
- }
-
- auto lhs_it = std::find_if(lhs.begin(), lhs.end(), [&rhs](auto& item)
- {
- return std::find(rhs.begin(), rhs.end(), item) == rhs.end();
- });
-
- return lhs_it == lhs.end();
-}
-
-// Checks that the given collection contains the specified item
-template <typename CollectionType>
-bool Contains(const CollectionType& collection, const typename CollectionType::value_type& item)
-{
- return std::find(collection.begin(), collection.end(), item) != collection.end();
-}
-
-// Checks that the given map contains the specified key
-template <typename MapType>
-bool Contains(const MapType& map, const typename MapType::key_type& key)
-{
- return map.find(key) != map.end();
-}
-
-// Utility template for comparing tensor elements
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-inline bool Compare(T a, T b, float tolerance = 0.000001f)
-{
- if (ArmnnType == armnn::DataType::Boolean)
- {
- // NOTE: Boolean is represented as uint8_t (with zero equals
- // false and everything else equals true), therefore values
- // need to be casted to bool before comparing them
- return static_cast<bool>(a) == static_cast<bool>(b);
- }
-
- // NOTE: All other types can be cast to float and compared with
- // a certain level of tolerance
- return std::fabs(static_cast<float>(a) - static_cast<float>(b)) <= tolerance;
-}
-
-template <typename ConvolutionLayer>
-void SetWeightAndBias(ConvolutionLayer* layer, const armnn::TensorInfo& weightInfo, const armnn::TensorInfo& biasInfo)
-{
- layer->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weightInfo);
- layer->m_Bias = std::make_unique<armnn::ScopedTensorHandle>(biasInfo);
-
- layer->m_Weight->Allocate();
- layer->m_Bias->Allocate();
-}
-
-armnn::SubgraphView::InputSlots CreateInputsFrom(const std::vector<armnn::Layer*>& layers);
-
-armnn::SubgraphView::OutputSlots CreateOutputsFrom(const std::vector<armnn::Layer*>& layers);
-
-armnn::SubgraphView::SubgraphViewPtr CreateSubgraphViewFrom(armnn::SubgraphView::InputSlots&& inputs,
- armnn::SubgraphView::OutputSlots&& outputs,
- armnn::SubgraphView::Layers&& layers);
-
-armnn::IBackendInternalUniquePtr CreateBackendObject(const armnn::BackendId& backendId);
-
-armnn::TensorShape MakeTensorShape(unsigned int batches,
- unsigned int channels,
- unsigned int height,
- unsigned int width,
- armnn::DataLayout layout);
-
-template<typename DataType>
-static std::vector<DataType> GenerateRandomData(size_t size)
-{
- constexpr bool isIntegerType = std::is_integral<DataType>::value;
- using Distribution =
- typename std::conditional<isIntegerType,
- std::uniform_int_distribution<DataType>,
- std::uniform_real_distribution<DataType>>::type;
-
- static constexpr DataType lowerLimit = std::numeric_limits<DataType>::min();
- static constexpr DataType upperLimit = std::numeric_limits<DataType>::max();
-
- static Distribution distribution(lowerLimit, upperLimit);
- static std::default_random_engine generator;
-
- std::vector<DataType> randomData(size);
- generate(randomData.begin(), randomData.end(), []() { return distribution(generator); });
-
- return randomData;
-}
+#pragma message("backendsCommon/test/CommonTestUtils.hpp has been deprecated, it is due for removal in 22.08 release." \
+ " Please use from armnnTestUtils library, /src/armnnTestUtils/CommonTestUtils.hpp)
\ No newline at end of file
diff --git a/src/backends/backendsCommon/test/ComparisonEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ComparisonEndToEndTestImpl.hpp
index e274163..4bdf3f8 100644
--- a/src/backends/backendsCommon/test/ComparisonEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/ComparisonEndToEndTestImpl.hpp
@@ -4,7 +4,7 @@
//
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/ConcatEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ConcatEndToEndTestImpl.hpp
index 62f0e4c..c8d20da 100644
--- a/src/backends/backendsCommon/test/ConcatEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/ConcatEndToEndTestImpl.hpp
@@ -4,7 +4,7 @@
//
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/Convolution3dEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/Convolution3dEndToEndTestImpl.hpp
index b1f685b..fab5670 100644
--- a/src/backends/backendsCommon/test/Convolution3dEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/Convolution3dEndToEndTestImpl.hpp
@@ -9,8 +9,8 @@
#include <ResolveType.hpp>
-#include <backendsCommon/test/CommonTestUtils.hpp>
-#include <backendsCommon/test/DataLayoutUtils.hpp>
+#include <CommonTestUtils.hpp>
+#include <armnnTestUtils/DataLayoutUtils.hpp>
#include <map>
#include <vector>
diff --git a/src/backends/backendsCommon/test/DataLayoutUtils.hpp b/src/backends/backendsCommon/test/DataLayoutUtils.hpp
index 89b3900..e920c54 100644
--- a/src/backends/backendsCommon/test/DataLayoutUtils.hpp
+++ b/src/backends/backendsCommon/test/DataLayoutUtils.hpp
@@ -1,60 +1,9 @@
//
-// Copyright © 2019 Arm Ltd. All rights reserved.
+// Copyright © 2019 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
+#include <armnnTestUtils/DataLayoutUtils.hpp>
-#include <armnn/Tensor.hpp>
-#include <armnn/Types.hpp>
-
-#include <armnnUtils/Permute.hpp>
-
-template<typename T>
-void PermuteTensorNchwToNhwc(armnn::TensorInfo& tensorInfo, std::vector<T>& tensorData)
-{
- const armnn::PermutationVector nchwToNhwc = { 0, 3, 1, 2 };
-
- tensorInfo = armnnUtils::Permuted(tensorInfo, nchwToNhwc);
-
- std::vector<T> tmp(tensorData.size());
- armnnUtils::Permute(tensorInfo.GetShape(), nchwToNhwc, tensorData.data(), tmp.data(), sizeof(T));
- tensorData = tmp;
-}
-
-template<typename T>
-void PermuteTensorNhwcToNchw(armnn::TensorInfo& tensorInfo, std::vector<T>& tensorData)
-{
- const armnn::PermutationVector nhwcToNchw = { 0, 2, 3, 1 };
-
- tensorInfo = armnnUtils::Permuted(tensorInfo, nhwcToNchw);
-
- std::vector<T> tmp(tensorData.size());
- armnnUtils::Permute(tensorInfo.GetShape(), nhwcToNchw, tensorData.data(), tmp.data(), sizeof(T));
-
- tensorData = tmp;
-}
-
-template<typename T>
-void PermuteTensorNdhwcToNcdhw(armnn::TensorInfo& tensorInfo, std::vector<T>& tensorData)
-{
- const armnn::PermutationVector ndhwcToNcdhw = { 0, 2, 3, 4, 1 };
-
- tensorInfo = armnnUtils::Permuted(tensorInfo, ndhwcToNcdhw);
-
- std::vector<T> tmp(tensorData.size());
- armnnUtils::Permute(tensorInfo.GetShape(), ndhwcToNcdhw, tensorData.data(), tmp.data(), sizeof(T));
- tensorData = tmp;
-}
-
-template<typename T>
-void PermuteTensorNcdhwToNdhwc(armnn::TensorInfo& tensorInfo, std::vector<T>& tensorData)
-{
- const armnn::PermutationVector ncdhwToNdhwc = { 0, 4, 1, 2, 3 };
-
- tensorInfo = armnnUtils::Permuted(tensorInfo, ncdhwToNdhwc);
-
- std::vector<T> tmp(tensorData.size());
- armnnUtils::Permute(tensorInfo.GetShape(), ncdhwToNdhwc, tensorData.data(), tmp.data(), sizeof(T));
- tensorData = tmp;
-}
+#pragma message("backendsCommon/test/DataLayoutUtils.hpp has been deprecated, it is due for removal " \
+ "in 22.08 release. Please use public interface include/armnnTestUtils/DataLayoutUtils.hpp")
diff --git a/src/backends/backendsCommon/test/DataTypeUtils.hpp b/src/backends/backendsCommon/test/DataTypeUtils.hpp
index cf97c81..03ee1d2 100644
--- a/src/backends/backendsCommon/test/DataTypeUtils.hpp
+++ b/src/backends/backendsCommon/test/DataTypeUtils.hpp
@@ -1,45 +1,9 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
+#include "../../armnnTestUtils/DataTypeUtils.hpp"
-#include <ResolveType.hpp>
-
-
-#include <reference/workloads/Encoders.hpp>
-
-#include <vector>
-
-// Utility tenmplate to convert a collection of values to the correct type
-template <armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-std::vector<T> ConvertToDataType(const std::vector<float>& input,
- const armnn::TensorInfo& inputTensorInfo)
-{
- std::vector<T> output(input.size());
- auto outputTensorInfo = inputTensorInfo;
- outputTensorInfo.SetDataType(ArmnnType);
-
- std::unique_ptr<armnn::Encoder<float>> pOutputEncoder = armnn::MakeEncoder<float>(outputTensorInfo, output.data());
- armnn::Encoder<float>& rOutputEncoder = *pOutputEncoder;
-
- for (auto it = input.begin(); it != input.end(); ++it)
- {
- rOutputEncoder.Set(*it);
- ++rOutputEncoder;
- }
- return output;
-}
-
-// Utility tenmplate to convert a single value to the correct type
-template <typename T>
-T ConvertToDataType(const float& value,
- const armnn::TensorInfo& tensorInfo)
-{
- std::vector<T> output(1);
- std::unique_ptr<armnn::Encoder<float>> pEncoder = armnn::MakeEncoder<float>(tensorInfo, output.data());
- armnn::Encoder<float>& rEncoder = *pEncoder;
- rEncoder.Set(value);
- return output[0];
-}
+#pragma message("backendsCommon/test/DataTypeUtils.hpp has been deprecated, it is due for removal in 22.08 release." \
+ " Please use from armnnTestUtils library, /src/armnnTestUtils/DataTypeUtils.hpp)
diff --git a/src/backends/backendsCommon/test/DepthToSpaceEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/DepthToSpaceEndToEndTestImpl.hpp
index b64e618..863d66c 100644
--- a/src/backends/backendsCommon/test/DepthToSpaceEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/DepthToSpaceEndToEndTestImpl.hpp
@@ -10,7 +10,7 @@
#include <QuantizeHelper.hpp>
-#include <backendsCommon/test/DataLayoutUtils.hpp>
+#include <armnnTestUtils/DataLayoutUtils.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/DequantizeEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/DequantizeEndToEndTestImpl.hpp
index fff4c4f..439c083 100644
--- a/src/backends/backendsCommon/test/DequantizeEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/DequantizeEndToEndTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <armnn/INetwork.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/DetectionPostProcessEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/DetectionPostProcessEndToEndTestImpl.hpp
index c448886..0f6d2c0 100644
--- a/src/backends/backendsCommon/test/DetectionPostProcessEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/DetectionPostProcessEndToEndTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <armnn/INetwork.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/DynamicBackendTests.cpp b/src/backends/backendsCommon/test/DynamicBackendTests.cpp
index 669ce60..72688ad 100644
--- a/src/backends/backendsCommon/test/DynamicBackendTests.cpp
+++ b/src/backends/backendsCommon/test/DynamicBackendTests.cpp
@@ -5,7 +5,7 @@
#include "DynamicBackendTests.hpp"
-#include <test/UnitTests.hpp>
+#include <UnitTests.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/ElementwiseUnaryEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ElementwiseUnaryEndToEndTestImpl.hpp
index 635dc96..3f530cc 100644
--- a/src/backends/backendsCommon/test/ElementwiseUnaryEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/ElementwiseUnaryEndToEndTestImpl.hpp
@@ -4,7 +4,7 @@
//
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
index 269a460..d326631 100644
--- a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
@@ -4,7 +4,7 @@
//
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <armnn/Descriptors.hpp>
#include <armnn/INetwork.hpp>
diff --git a/src/backends/backendsCommon/test/FillEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/FillEndToEndTestImpl.hpp
index 27e5aa0..53722e1 100644
--- a/src/backends/backendsCommon/test/FillEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/FillEndToEndTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <armnn/INetwork.hpp>
#include <armnn/TypesUtils.hpp>
diff --git a/src/backends/backendsCommon/test/FullyConnectedEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/FullyConnectedEndToEndTestImpl.hpp
index 878b6af..1076aa6 100644
--- a/src/backends/backendsCommon/test/FullyConnectedEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/FullyConnectedEndToEndTestImpl.hpp
@@ -4,7 +4,7 @@
//
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/GatherEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/GatherEndToEndTestImpl.hpp
index 4c67ec2..cf42947 100644
--- a/src/backends/backendsCommon/test/GatherEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/GatherEndToEndTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <armnn/INetwork.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/InstanceNormalizationEndToEndTestImpl.cpp b/src/backends/backendsCommon/test/InstanceNormalizationEndToEndTestImpl.cpp
index e715e6b..846aa76 100644
--- a/src/backends/backendsCommon/test/InstanceNormalizationEndToEndTestImpl.cpp
+++ b/src/backends/backendsCommon/test/InstanceNormalizationEndToEndTestImpl.cpp
@@ -12,9 +12,9 @@
#include <armnn/INetwork.hpp>
-#include <backendsCommon/test/DataLayoutUtils.hpp>
+#include <armnnTestUtils/DataLayoutUtils.hpp>
-#include <test/TestUtils.hpp>
+#include <TestUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp b/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp
index 579be51..f55a3c3 100644
--- a/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp
+++ b/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <Graph.hpp>
diff --git a/src/backends/backendsCommon/test/LogSoftmaxEndToEndTestImpl.cpp b/src/backends/backendsCommon/test/LogSoftmaxEndToEndTestImpl.cpp
index 181ecd9..9ffa2a6 100644
--- a/src/backends/backendsCommon/test/LogSoftmaxEndToEndTestImpl.cpp
+++ b/src/backends/backendsCommon/test/LogSoftmaxEndToEndTestImpl.cpp
@@ -8,7 +8,7 @@
#include <armnn/INetwork.hpp>
-#include <test/TestUtils.hpp>
+#include <TestUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/OptimizationViewsTests.cpp b/src/backends/backendsCommon/test/OptimizationViewsTests.cpp
index 246cb50..bbae229 100644
--- a/src/backends/backendsCommon/test/OptimizationViewsTests.cpp
+++ b/src/backends/backendsCommon/test/OptimizationViewsTests.cpp
@@ -4,7 +4,7 @@
//
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include "MockBackend.hpp"
#include <armnn/backends/OptimizationViews.hpp>
diff --git a/src/backends/backendsCommon/test/OptimizeSubgraphViewTests.cpp b/src/backends/backendsCommon/test/OptimizeSubgraphViewTests.cpp
index 6c76da6..4dd6bc9 100644
--- a/src/backends/backendsCommon/test/OptimizeSubgraphViewTests.cpp
+++ b/src/backends/backendsCommon/test/OptimizeSubgraphViewTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include "MockBackend.hpp"
#include "MockBackendId.hpp"
diff --git a/src/backends/backendsCommon/test/OptimizedNetworkTests.cpp b/src/backends/backendsCommon/test/OptimizedNetworkTests.cpp
index 4b932c7..cc79741 100644
--- a/src/backends/backendsCommon/test/OptimizedNetworkTests.cpp
+++ b/src/backends/backendsCommon/test/OptimizedNetworkTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <Graph.hpp>
#include <Network.hpp>
diff --git a/src/backends/backendsCommon/test/PreluEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/PreluEndToEndTestImpl.hpp
index c31d084..b361511 100644
--- a/src/backends/backendsCommon/test/PreluEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/PreluEndToEndTestImpl.hpp
@@ -8,7 +8,7 @@
#include <armnn/INetwork.hpp>
-#include <backendsCommon/test/CommonTestUtils.hpp>
+#include <CommonTestUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/QLstmEndToEndTestImpl.cpp b/src/backends/backendsCommon/test/QLstmEndToEndTestImpl.cpp
index 7c87f35..a01f65e 100644
--- a/src/backends/backendsCommon/test/QLstmEndToEndTestImpl.cpp
+++ b/src/backends/backendsCommon/test/QLstmEndToEndTestImpl.cpp
@@ -5,7 +5,7 @@
#include "QLstmEndToEndTestImpl.hpp"
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include "EndToEndTestImpl.hpp"
#include <armnn/INetwork.hpp>
diff --git a/src/backends/backendsCommon/test/QuantizedLstmEndToEndTestImpl.cpp b/src/backends/backendsCommon/test/QuantizedLstmEndToEndTestImpl.cpp
index d481404..8a535d2 100644
--- a/src/backends/backendsCommon/test/QuantizedLstmEndToEndTestImpl.cpp
+++ b/src/backends/backendsCommon/test/QuantizedLstmEndToEndTestImpl.cpp
@@ -5,7 +5,7 @@
#include "QuantizedLstmEndToEndTestImpl.hpp"
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include "EndToEndTestImpl.hpp"
#include <ResolveType.hpp>
@@ -15,7 +15,7 @@
#include <armnn/utility/NumericCast.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/RankEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/RankEndToEndTestImpl.hpp
index 5229c47..9dcf705 100644
--- a/src/backends/backendsCommon/test/RankEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/RankEndToEndTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "CommonTestUtils.hpp"
+#include <CommonTestUtils.hpp>
#include <armnn/INetwork.hpp>
#include <armnn/TypesUtils.hpp>
diff --git a/src/backends/backendsCommon/test/ResizeEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ResizeEndToEndTestImpl.hpp
index a56db44..94d0a4d 100644
--- a/src/backends/backendsCommon/test/ResizeEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/ResizeEndToEndTestImpl.hpp
@@ -12,7 +12,7 @@
#include <QuantizeHelper.hpp>
#include <ResolveType.hpp>
-#include <backendsCommon/test/CommonTestUtils.hpp>
+#include <CommonTestUtils.hpp>
#include <map>
#include <vector>
diff --git a/src/backends/backendsCommon/test/SpaceToDepthEndToEndTestImpl.cpp b/src/backends/backendsCommon/test/SpaceToDepthEndToEndTestImpl.cpp
index e3b016e..b868ba3 100644
--- a/src/backends/backendsCommon/test/SpaceToDepthEndToEndTestImpl.cpp
+++ b/src/backends/backendsCommon/test/SpaceToDepthEndToEndTestImpl.cpp
@@ -12,9 +12,9 @@
#include <armnnUtils/Permute.hpp>
#include <armnnUtils/DataLayoutIndexed.hpp>
-#include <backendsCommon/test/DataLayoutUtils.hpp>
+#include <armnnTestUtils/DataLayoutUtils.hpp>
-#include <test/TestUtils.hpp>
+#include <TestUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/SplitterEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/SplitterEndToEndTestImpl.hpp
index 3a2af68..b750a7a 100644
--- a/src/backends/backendsCommon/test/SplitterEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/SplitterEndToEndTestImpl.hpp
@@ -10,7 +10,7 @@
#include <armnn/utility/NumericCast.hpp>
-#include <backendsCommon/test/CommonTestUtils.hpp>
+#include <CommonTestUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/StridedSliceAsyncEndToEndTest.hpp b/src/backends/backendsCommon/test/StridedSliceAsyncEndToEndTest.hpp
index 8ef5ecc..e29782f 100644
--- a/src/backends/backendsCommon/test/StridedSliceAsyncEndToEndTest.hpp
+++ b/src/backends/backendsCommon/test/StridedSliceAsyncEndToEndTest.hpp
@@ -13,7 +13,7 @@
#include <armnn/IAsyncExecutionCallback.hpp>
#include <AsyncExecutionCallback.hpp>
-#include <backendsCommon/test/CommonTestUtils.hpp>
+#include <CommonTestUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/TensorCopyUtils.hpp b/src/backends/backendsCommon/test/TensorCopyUtils.hpp
index d3c8d90..e0aa7a0 100644
--- a/src/backends/backendsCommon/test/TensorCopyUtils.hpp
+++ b/src/backends/backendsCommon/test/TensorCopyUtils.hpp
@@ -1,15 +1,9 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
-#include <armnn/Tensor.hpp>
-
-#include <armnn/backends/ITensorHandle.hpp>
-
-void CopyDataToITensorHandle(armnn::ITensorHandle* tensorHandle, const void* memory);
-
-void CopyDataFromITensorHandle(void* mem, const armnn::ITensorHandle* tensorHandle);
-
-void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle* tensorHandle, const void* memory);
\ No newline at end of file
+// This file is deprecated and will be removed soon.
+// Please use the new header in armnnTestUtils instead.
+// This will use the new armnnTestUtils header.
+#include <armnnTestUtils/TesnorCopyUtils.hpp>
\ No newline at end of file
diff --git a/src/backends/backendsCommon/test/TransposeConvolution2dEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/TransposeConvolution2dEndToEndTestImpl.hpp
index 8f10869..d1b6945 100644
--- a/src/backends/backendsCommon/test/TransposeConvolution2dEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/TransposeConvolution2dEndToEndTestImpl.hpp
@@ -12,7 +12,7 @@
#include <QuantizeHelper.hpp>
#include <ResolveType.hpp>
-#include <backendsCommon/test/CommonTestUtils.hpp>
+#include <CommonTestUtils.hpp>
#include <map>
#include <vector>
diff --git a/src/backends/backendsCommon/test/WorkloadDataValidation.cpp b/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
index a19d12f..ee632ff 100644
--- a/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
+++ b/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "WorkloadTestUtils.hpp"
+#include <WorkloadTestUtils.hpp>
#include <armnn/Exceptions.hpp>
diff --git a/src/backends/backendsCommon/test/WorkloadTestUtils.hpp b/src/backends/backendsCommon/test/WorkloadTestUtils.hpp
index 3173561..cb605af 100644
--- a/src/backends/backendsCommon/test/WorkloadTestUtils.hpp
+++ b/src/backends/backendsCommon/test/WorkloadTestUtils.hpp
@@ -1,113 +1,9 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
-#include <armnn/Tensor.hpp>
-
-#include <armnn/backends/IBackendInternal.hpp>
-#include <armnn/backends/IMemoryManager.hpp>
-#include <backendsCommon/Workload.hpp>
-#include <backendsCommon/WorkloadInfo.hpp>
-
-namespace armnn
-{
-class ITensorHandle;
-} // namespace armnn
-
-namespace
-{
-
-template <typename QueueDescriptor>
-void AddInputToWorkload(QueueDescriptor& descriptor,
- armnn::WorkloadInfo& info,
- const armnn::TensorInfo& tensorInfo,
- armnn::ITensorHandle* tensorHandle)
-{
- descriptor.m_Inputs.push_back(tensorHandle);
- info.m_InputTensorInfos.push_back(tensorInfo);
-}
-
-template <typename QueueDescriptor>
-void AddOutputToWorkload(QueueDescriptor& descriptor,
- armnn::WorkloadInfo& info,
- const armnn::TensorInfo& tensorInfo,
- armnn::ITensorHandle* tensorHandle)
-{
- descriptor.m_Outputs.push_back(tensorHandle);
- info.m_OutputTensorInfos.push_back(tensorInfo);
-}
-
-template <typename QueueDescriptor>
-void SetWorkloadInput(QueueDescriptor& descriptor,
- armnn::WorkloadInfo& info,
- unsigned int index,
- const armnn::TensorInfo& tensorInfo,
- armnn::ITensorHandle* tensorHandle)
-{
- descriptor.m_Inputs[index] = tensorHandle;
- info.m_InputTensorInfos[index] = tensorInfo;
-}
-
-template <typename QueueDescriptor>
-void SetWorkloadOutput(QueueDescriptor& descriptor,
- armnn::WorkloadInfo& info,
- unsigned int index,
- const armnn::TensorInfo& tensorInfo,
- armnn::ITensorHandle* tensorHandle)
-{
- descriptor.m_Outputs[index] = tensorHandle;
- info.m_OutputTensorInfos[index] = tensorInfo;
-}
-
-inline void ExecuteWorkload(armnn::IWorkload& workload,
- const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- bool memoryManagementRequested = true)
-{
- const bool manageMemory = memoryManager && memoryManagementRequested;
-
- // Acquire working memory (if needed)
- if (manageMemory)
- {
- memoryManager->Acquire();
- }
-
- // Perform PostAllocationConfiguration
- workload.PostAllocationConfigure();
-
- // Execute the workload
- workload.Execute();
-
- // Release working memory (if needed)
- if (manageMemory)
- {
- memoryManager->Release();
- }
-}
-
-inline armnn::Optional<armnn::DataType> GetBiasTypeFromWeightsType(armnn::Optional<armnn::DataType> weightsType)
-{
- if (!weightsType)
- {
- return weightsType;
- }
-
- switch(weightsType.value())
- {
- case armnn::DataType::BFloat16:
- case armnn::DataType::Float16:
- case armnn::DataType::Float32:
- return weightsType;
- case armnn::DataType::QAsymmS8:
- case armnn::DataType::QAsymmU8:
- case armnn::DataType::QSymmS8:
- case armnn::DataType::QSymmS16:
- return armnn::DataType::Signed32;
- default:
- ARMNN_ASSERT_MSG(false, "GetBiasTypeFromWeightsType(): Unsupported data type.");
- }
- return armnn::EmptyOptional();
-}
-
-} // anonymous namespace
+// This file is deprecated and will be removed soon.
+// Please use the new header in armnnTestUtils instead.
+// This will use the new armnnTestUtils header.
+#include "../../../armnnTestUtils/WorkloadTestUtils.hpp"
diff --git a/src/backends/backendsCommon/test/layerTests/AbsTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/AbsTestImpl.hpp
index 44dd9ce..7f2d1be 100644
--- a/src/backends/backendsCommon/test/layerTests/AbsTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/AbsTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp
index 5405207..5ec8e13 100644
--- a/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp
@@ -9,13 +9,13 @@
#include <ResolveType.hpp>
#include <backendsCommon/test/ActivationFixture.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
#include <reference/test/RefWorkloadFactoryHelper.hpp>
#include <armnn/utility/NumericCast.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <algorithm>
diff --git a/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.hpp
index a65d97c..9e8b3a2 100644
--- a/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/AdditionTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/AdditionTestImpl.hpp
index b6d6e4a..a66d474 100644
--- a/src/backends/backendsCommon/test/layerTests/AdditionTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/AdditionTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ArgMinMaxTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ArgMinMaxTestImpl.cpp
index 34b2539..4f82b59 100644
--- a/src/backends/backendsCommon/test/layerTests/ArgMinMaxTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ArgMinMaxTestImpl.cpp
@@ -6,11 +6,11 @@
#include "ArgMinMaxTestImpl.hpp"
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/ArgMinMaxTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ArgMinMaxTestImpl.hpp
index 2e7a54b..9414705 100644
--- a/src/backends/backendsCommon/test/layerTests/ArgMinMaxTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ArgMinMaxTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.cpp
index 4311faf..90bc8d7 100644
--- a/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.cpp
@@ -16,10 +16,10 @@
#include <backendsCommon/WorkloadFactory.hpp>
#include <reference/test/RefWorkloadFactoryHelper.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.hpp
index f57c061..11bc297 100644
--- a/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/BatchToSpaceNdTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/BatchToSpaceNdTestImpl.hpp
index 3669281..19d472b 100644
--- a/src/backends/backendsCommon/test/layerTests/BatchToSpaceNdTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/BatchToSpaceNdTestImpl.hpp
@@ -5,19 +5,16 @@
#pragma once
-#include "LayerTestResult.hpp"
-
#include <ResolveType.hpp>
-
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
-
-#include <test/TensorHelpers.hpp>
+#include <armnnTestUtils/LayerTestResult.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <TensorHelpers.hpp>
+#include <WorkloadTestUtils.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/CastTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/CastTestImpl.hpp
index bf8d5a4..5569098 100644
--- a/src/backends/backendsCommon/test/layerTests/CastTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/CastTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ChannelShuffleTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ChannelShuffleTestImpl.cpp
index b026b4e..598f205 100644
--- a/src/backends/backendsCommon/test/layerTests/ChannelShuffleTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ChannelShuffleTestImpl.cpp
@@ -5,9 +5,9 @@
#include "ChannelShuffleTestImpl.hpp"
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/ChannelShuffleTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ChannelShuffleTestImpl.hpp
index 3500e72..9c5f40d 100644
--- a/src/backends/backendsCommon/test/layerTests/ChannelShuffleTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ChannelShuffleTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp
index 68bc588..5eccd01 100644
--- a/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp
@@ -13,10 +13,10 @@
#include <backendsCommon/Workload.hpp>
#include <backendsCommon/WorkloadData.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.hpp
index 3012417..8a920e5 100644
--- a/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp
index 3eca273..5238729 100644
--- a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp
@@ -11,10 +11,10 @@
#include <armnnUtils/Permute.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
using namespace armnn;
using namespace armnnUtils;
diff --git a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.hpp
index 64e0c0a..c91ee86 100644
--- a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <BFloat16.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp
index bb827ef..dd339ba 100644
--- a/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp
@@ -13,10 +13,10 @@
#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.hpp
index 71aacb5..34491b1 100644
--- a/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
index 99f1436..61e000a 100644
--- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
@@ -15,11 +15,11 @@
#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/test/DataLayoutUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/DataLayoutUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <string>
diff --git a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.hpp
index 1f54034..f54a6f8 100644
--- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/Conv3dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Conv3dTestImpl.cpp
index a592ea3..4adc6ef 100644
--- a/src/backends/backendsCommon/test/layerTests/Conv3dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Conv3dTestImpl.cpp
@@ -11,11 +11,11 @@
#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/test/DataLayoutUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/DataLayoutUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
using namespace armnnUtils;
diff --git a/src/backends/backendsCommon/test/layerTests/Conv3dTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/Conv3dTestImpl.hpp
index c612e19..127e7ef 100644
--- a/src/backends/backendsCommon/test/layerTests/Conv3dTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/Conv3dTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ConvertBf16ToFp32TestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConvertBf16ToFp32TestImpl.cpp
index b16ce47..7699daa 100644
--- a/src/backends/backendsCommon/test/layerTests/ConvertBf16ToFp32TestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ConvertBf16ToFp32TestImpl.cpp
@@ -5,10 +5,10 @@
#include "ConvertBf16ToFp32TestImpl.hpp"
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
LayerTestResult<float, 4> ConvertBf16ToFp32Test(
armnn::IWorkloadFactory& workloadFactory,
diff --git a/src/backends/backendsCommon/test/layerTests/ConvertBf16ToFp32TestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ConvertBf16ToFp32TestImpl.hpp
index 08f4c04..db92d42 100644
--- a/src/backends/backendsCommon/test/layerTests/ConvertBf16ToFp32TestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ConvertBf16ToFp32TestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <BFloat16.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ConvertFp16ToFp32TestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConvertFp16ToFp32TestImpl.cpp
index 177acef..2c1f9b9 100644
--- a/src/backends/backendsCommon/test/layerTests/ConvertFp16ToFp32TestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ConvertFp16ToFp32TestImpl.cpp
@@ -8,10 +8,10 @@
#include <Half.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
LayerTestResult<float, 4> SimpleConvertFp16ToFp32Test(
armnn::IWorkloadFactory& workloadFactory,
diff --git a/src/backends/backendsCommon/test/layerTests/ConvertFp16ToFp32TestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ConvertFp16ToFp32TestImpl.hpp
index 8eefb77..9e64cdd 100644
--- a/src/backends/backendsCommon/test/layerTests/ConvertFp16ToFp32TestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ConvertFp16ToFp32TestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ConvertFp32ToBf16TestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConvertFp32ToBf16TestImpl.cpp
index 9ab3746..14a75c1 100644
--- a/src/backends/backendsCommon/test/layerTests/ConvertFp32ToBf16TestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ConvertFp32ToBf16TestImpl.cpp
@@ -5,10 +5,10 @@
#include "ConvertFp32ToBf16TestImpl.hpp"
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
LayerTestResult<armnn::BFloat16, 4> ConvertFp32ToBf16Test(
armnn::IWorkloadFactory& workloadFactory,
diff --git a/src/backends/backendsCommon/test/layerTests/ConvertFp32ToBf16TestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ConvertFp32ToBf16TestImpl.hpp
index 9e1da65..737181d 100644
--- a/src/backends/backendsCommon/test/layerTests/ConvertFp32ToBf16TestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ConvertFp32ToBf16TestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <BFloat16.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ConvertFp32ToFp16TestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConvertFp32ToFp16TestImpl.cpp
index 9946801..8210b2d 100644
--- a/src/backends/backendsCommon/test/layerTests/ConvertFp32ToFp16TestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ConvertFp32ToFp16TestImpl.cpp
@@ -6,10 +6,10 @@
#include "ConvertFp32ToFp16TestImpl.hpp"
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
LayerTestResult<armnn::Half, 4> SimpleConvertFp32ToFp16Test(
armnn::IWorkloadFactory& workloadFactory,
diff --git a/src/backends/backendsCommon/test/layerTests/ConvertFp32ToFp16TestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ConvertFp32ToFp16TestImpl.hpp
index 39dc8a4..8b6617c 100644
--- a/src/backends/backendsCommon/test/layerTests/ConvertFp32ToFp16TestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ConvertFp32ToFp16TestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/DebugTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/DebugTestImpl.cpp
index 0539cd1..5475dbf 100644
--- a/src/backends/backendsCommon/test/layerTests/DebugTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/DebugTestImpl.cpp
@@ -9,10 +9,10 @@
#include <ResolveType.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/layerTests/DebugTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/DebugTestImpl.hpp
index cf4b237..beab583 100644
--- a/src/backends/backendsCommon/test/layerTests/DebugTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/DebugTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <BFloat16.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp
index 7495c6b..be88e77 100644
--- a/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp
@@ -8,11 +8,11 @@
#include <QuantizeHelper.hpp>
-#include <backendsCommon/test/DataLayoutUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/DataLayoutUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.hpp
index 18797c6..c6781a9 100644
--- a/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.hpp
@@ -4,7 +4,7 @@
//
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/DequantizeTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/DequantizeTestImpl.cpp
index 924844d..61fb407 100644
--- a/src/backends/backendsCommon/test/layerTests/DequantizeTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/DequantizeTestImpl.cpp
@@ -8,10 +8,10 @@
#include <ResolveType.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/DequantizeTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/DequantizeTestImpl.hpp
index 1e079a7..8f120d3 100644
--- a/src/backends/backendsCommon/test/layerTests/DequantizeTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/DequantizeTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp
index 2472c34..b9f06de 100644
--- a/src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp
@@ -12,11 +12,11 @@
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
#include <backendsCommon/test/WorkloadFactoryHelper.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/layerTests/DivisionTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/DivisionTestImpl.hpp
index 4146746..b5d04e5 100644
--- a/src/backends/backendsCommon/test/layerTests/DivisionTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/DivisionTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ElementwiseTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ElementwiseTestImpl.hpp
index 88f34f6..3175aaf 100644
--- a/src/backends/backendsCommon/test/layerTests/ElementwiseTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ElementwiseTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
@@ -15,11 +15,11 @@
#include <backendsCommon/WorkloadData.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <memory>
diff --git a/src/backends/backendsCommon/test/layerTests/ElementwiseUnaryTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ElementwiseUnaryTestImpl.hpp
index 20e341b..a15add0 100644
--- a/src/backends/backendsCommon/test/layerTests/ElementwiseUnaryTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ElementwiseUnaryTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/ArmNN.hpp>
@@ -16,11 +16,11 @@
#include <backendsCommon/WorkloadData.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <memory>
diff --git a/src/backends/backendsCommon/test/layerTests/ExpTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ExpTestImpl.hpp
index 91cb669..c7008a7 100644
--- a/src/backends/backendsCommon/test/layerTests/ExpTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ExpTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.cpp
index bbe4816..f433f9d 100644
--- a/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.cpp
@@ -8,10 +8,10 @@
#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
LayerTestResult<float, 2> FakeQuantizationTest(
armnn::IWorkloadFactory& workloadFactory,
diff --git a/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.hpp
index 519880e..d8af8c5 100644
--- a/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/FillTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/FillTestImpl.cpp
index 9208a31..41fcf59 100644
--- a/src/backends/backendsCommon/test/layerTests/FillTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/FillTestImpl.cpp
@@ -5,11 +5,11 @@
#include "FillTestImpl.hpp"
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
template<armnn::DataType ArmnnType, typename T>
LayerTestResult<T, 4> SimpleFillTest(
diff --git a/src/backends/backendsCommon/test/layerTests/FillTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/FillTestImpl.hpp
index 0eaffd1..beaf35c 100644
--- a/src/backends/backendsCommon/test/layerTests/FillTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/FillTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/FloorTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/FloorTestImpl.cpp
index bf871ae..c05e1d8 100644
--- a/src/backends/backendsCommon/test/layerTests/FloorTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/FloorTestImpl.cpp
@@ -5,11 +5,11 @@
#include "FloorTestImpl.hpp"
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
template<armnn::DataType ArmnnType, typename T>
LayerTestResult<T, 4> SimpleFloorTest(
diff --git a/src/backends/backendsCommon/test/layerTests/FloorTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/FloorTestImpl.hpp
index 78211c6..ff25252 100644
--- a/src/backends/backendsCommon/test/layerTests/FloorTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/FloorTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp
index dcf87fe..59e67fe 100644
--- a/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp
@@ -10,11 +10,11 @@
#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
//
// Implementation templates
diff --git a/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.hpp
index ec921f7..76cea90 100644
--- a/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/GatherTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/GatherTestImpl.cpp
index 51df1eb..edcc900 100644
--- a/src/backends/backendsCommon/test/layerTests/GatherTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/GatherTestImpl.cpp
@@ -8,10 +8,10 @@
#include <ResolveType.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/GatherTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/GatherTestImpl.hpp
index 8c37f92..363478d 100644
--- a/src/backends/backendsCommon/test/layerTests/GatherTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/GatherTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.cpp
index ed656da..da9608c 100644
--- a/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.cpp
@@ -13,11 +13,11 @@
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/DataLayoutUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/DataLayoutUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.hpp
index d28069a..be77144 100644
--- a/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.cpp
index 11c9766..67f1c3c 100644
--- a/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.cpp
@@ -11,10 +11,10 @@
#include <armnnUtils/TensorUtils.hpp>
#include <armnnUtils/Permute.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <numeric>
diff --git a/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.hpp
index 137ab7e..283a25b 100644
--- a/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/L2NormalizationTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/Types.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp b/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp
index ac60764..e0054ca 100644
--- a/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp
+++ b/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp
@@ -1,62 +1,15 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
-#pragma once
+// This file is deprecated and will be removed soon.
+// Please use the new header in armnnTestUtils instead.
+// This will use the new armnnTestUtils header.
+#include <armnnTestUtils/LayerTestResult.hpp>
-#include <armnn/Tensor.hpp>
-#include <armnn/utility/Assert.hpp>
-
-#include <cstddef>
-#include <vector>
-
-template <typename T, std::size_t n>
-struct LayerTestResult
-{
- LayerTestResult(const armnn::TensorInfo& outputInfo)
- : m_Supported(true)
- , m_CompareBoolean(false)
- {
- m_ActualData.reserve(outputInfo.GetNumElements());
- m_ExpectedData.reserve(outputInfo.GetNumElements());
- m_ActualShape = outputInfo.GetShape();
- m_ExpectedShape = outputInfo.GetShape();
- }
-
- LayerTestResult(const std::vector<T>& actualData,
- const std::vector<T>& expectedData,
- const armnn::TensorShape& actualShape,
- const armnn::TensorShape& expectedShape)
- : m_ActualData(actualData)
- , m_ExpectedData(expectedData)
- , m_ActualShape(actualShape)
- , m_ExpectedShape(expectedShape)
- , m_Supported(true)
- , m_CompareBoolean(false)
- {}
-
- LayerTestResult(const std::vector<T>& actualData,
- const std::vector<T>& expectedData,
- const armnn::TensorShape& actualShape,
- const armnn::TensorShape& expectedShape,
- const bool compareBoolean)
- : m_ActualData(actualData)
- , m_ExpectedData(expectedData)
- , m_ActualShape(actualShape)
- , m_ExpectedShape(expectedShape)
- , m_Supported(true)
- , m_CompareBoolean(compareBoolean)
- {}
-
- std::vector<T> m_ActualData;
- std::vector<T> m_ExpectedData;
- armnn::TensorShape m_ActualShape;
- armnn::TensorShape m_ExpectedShape;
-
- bool m_Supported;
- bool m_CompareBoolean;
-};
+#pragma message("backendsCommon/test/layerTests/LayerTestResult.hpp has been deprecated, it is due for " \
+ "removal in 22.08 release. Please use public interface include/armnnTestUtils/LayerTestResult.hpp")
diff --git a/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.cpp
index ad23f8f..94f5a5b 100644
--- a/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.cpp
@@ -14,10 +14,10 @@
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.hpp
index 1f4cc89..b293337 100644
--- a/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/LogTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/LogTestImpl.hpp
index e7e14b8..cf9878f 100644
--- a/src/backends/backendsCommon/test/layerTests/LogTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/LogTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/LogicalTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/LogicalTestImpl.cpp
index 119e76b..a2ce5af 100644
--- a/src/backends/backendsCommon/test/layerTests/LogicalTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/LogicalTestImpl.cpp
@@ -11,10 +11,10 @@
#include <backendsCommon/Workload.hpp>
#include <backendsCommon/WorkloadData.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace {
diff --git a/src/backends/backendsCommon/test/layerTests/LogicalTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/LogicalTestImpl.hpp
index 1711d90..b81d2f3 100644
--- a/src/backends/backendsCommon/test/layerTests/LogicalTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/LogicalTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp
index 035c592..56bc23c 100644
--- a/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp
@@ -11,14 +11,14 @@
#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
#include <reference/workloads/Decoders.hpp>
#include <reference/workloads/Encoders.hpp>
#include <reference/workloads/LstmUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <doctest/doctest.h>
namespace
diff --git a/src/backends/backendsCommon/test/layerTests/LstmTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/LstmTestImpl.hpp
index d27ddd6..62bb125 100644
--- a/src/backends/backendsCommon/test/layerTests/LstmTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/LstmTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/MaximumTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/MaximumTestImpl.hpp
index 8cc660b..c13059b 100644
--- a/src/backends/backendsCommon/test/layerTests/MaximumTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/MaximumTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/MeanTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/MeanTestImpl.hpp
index 0f045d1..9cc45e2 100644
--- a/src/backends/backendsCommon/test/layerTests/MeanTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/MeanTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/MinimumTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/MinimumTestImpl.hpp
index 1e84191..bd60b20 100644
--- a/src/backends/backendsCommon/test/layerTests/MinimumTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/MinimumTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/MirrorPadTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/MirrorPadTestImpl.cpp
index 61899db..60fbfb0 100644
--- a/src/backends/backendsCommon/test/layerTests/MirrorPadTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/MirrorPadTestImpl.cpp
@@ -7,10 +7,10 @@
#include <QuantizeHelper.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
//
// Implementation templates
diff --git a/src/backends/backendsCommon/test/layerTests/MirrorPadTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/MirrorPadTestImpl.hpp
index 52898b8..60475fd 100644
--- a/src/backends/backendsCommon/test/layerTests/MirrorPadTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/MirrorPadTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/MultiplicationTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/MultiplicationTestImpl.hpp
index 9d2a954..72154db 100644
--- a/src/backends/backendsCommon/test/layerTests/MultiplicationTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/MultiplicationTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/NegTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/NegTestImpl.hpp
index 126a754..0296ca2 100644
--- a/src/backends/backendsCommon/test/layerTests/NegTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/NegTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.cpp
index 153afd9..e3a3bea 100644
--- a/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.cpp
@@ -12,10 +12,10 @@
#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.hpp
index bbbbc4f..30cd57c 100644
--- a/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/Types.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/PadTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/PadTestImpl.cpp
index a09e387..628eed0 100644
--- a/src/backends/backendsCommon/test/layerTests/PadTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/PadTestImpl.cpp
@@ -7,10 +7,10 @@
#include <QuantizeHelper.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
//
// Implementation templates
diff --git a/src/backends/backendsCommon/test/layerTests/PadTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/PadTestImpl.hpp
index 4c30c42..1d19aa8 100644
--- a/src/backends/backendsCommon/test/layerTests/PadTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/PadTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/PermuteTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/PermuteTestImpl.hpp
index 91add54..26fb504 100644
--- a/src/backends/backendsCommon/test/layerTests/PermuteTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/PermuteTestImpl.hpp
@@ -11,9 +11,9 @@
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
template<typename T>
LayerTestResult<T, 4> SimplePermuteTestImpl(
diff --git a/src/backends/backendsCommon/test/layerTests/Pooling2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Pooling2dTestImpl.cpp
index 1eaf1f9..7bb0e59 100644
--- a/src/backends/backendsCommon/test/layerTests/Pooling2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Pooling2dTestImpl.cpp
@@ -19,10 +19,10 @@
#include <backendsCommon/WorkloadInfo.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/Pooling2dTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/Pooling2dTestImpl.hpp
index bf2c39e..0a25339 100644
--- a/src/backends/backendsCommon/test/layerTests/Pooling2dTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/Pooling2dTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/Types.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.cpp
index 96a56fd..ad438ea 100644
--- a/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.cpp
@@ -19,10 +19,10 @@
#include <armnn/BackendHelper.hpp>
#include <backendsCommon/WorkloadInfo.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.hpp
index e7cd6b4..6c1d5de 100644
--- a/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/Types.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/PreluTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/PreluTestImpl.hpp
index 3cf8581..6b9aaed 100644
--- a/src/backends/backendsCommon/test/layerTests/PreluTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/PreluTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <QuantizeHelper.hpp>
#include <ResolveType.hpp>
@@ -14,11 +14,11 @@
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
#include <backendsCommon/test/WorkloadFactoryHelper.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> PreluTest(
diff --git a/src/backends/backendsCommon/test/layerTests/QuantizeTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/QuantizeTestImpl.cpp
index 029d50e..b593620 100644
--- a/src/backends/backendsCommon/test/layerTests/QuantizeTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/QuantizeTestImpl.cpp
@@ -11,10 +11,10 @@
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/QuantizeTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/QuantizeTestImpl.hpp
index 9e2f3df..9671550 100644
--- a/src/backends/backendsCommon/test/layerTests/QuantizeTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/QuantizeTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/RankTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/RankTestImpl.cpp
index c483d2c..c04d7b2 100644
--- a/src/backends/backendsCommon/test/layerTests/RankTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/RankTestImpl.cpp
@@ -5,11 +5,11 @@
#include "RankTestImpl.hpp"
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
template<typename T, std::size_t n>
LayerTestResult<int32_t, 1> RankTest(
diff --git a/src/backends/backendsCommon/test/layerTests/RankTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/RankTestImpl.hpp
index 0aacee1..27b0fcc 100644
--- a/src/backends/backendsCommon/test/layerTests/RankTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/RankTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.cpp
index 4fb0732..b93eb55 100644
--- a/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.cpp
@@ -5,11 +5,11 @@
#include "ReduceProdTestImpl.hpp"
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.hpp
index 97e9497..4d7ddde 100644
--- a/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.cpp
index 9f5422b..c50fe75 100644
--- a/src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.cpp
@@ -5,11 +5,11 @@
#include "ReduceSumTestImpl.hpp"
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.hpp
index db23240..a5249b4 100644
--- a/src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ReductionTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ReductionTestImpl.cpp
index 7ce03ad..a69afb8 100644
--- a/src/backends/backendsCommon/test/layerTests/ReductionTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ReductionTestImpl.cpp
@@ -5,11 +5,11 @@
#include "ReductionTestImpl.hpp"
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <iostream>
diff --git a/src/backends/backendsCommon/test/layerTests/ReductionTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ReductionTestImpl.hpp
index 495a74b..1480935 100644
--- a/src/backends/backendsCommon/test/layerTests/ReductionTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ReductionTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ReshapeTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ReshapeTestImpl.cpp
index c3aacad..ccf2345 100644
--- a/src/backends/backendsCommon/test/layerTests/ReshapeTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ReshapeTestImpl.cpp
@@ -5,11 +5,11 @@
#include "ReshapeTestImpl.hpp"
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/ReshapeTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ReshapeTestImpl.hpp
index a29a965..c692c95 100644
--- a/src/backends/backendsCommon/test/layerTests/ReshapeTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ReshapeTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ResizeTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ResizeTestImpl.cpp
index 7706bde..aa5bbae 100644
--- a/src/backends/backendsCommon/test/layerTests/ResizeTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ResizeTestImpl.cpp
@@ -12,11 +12,11 @@
#include <armnnUtils/DataLayoutIndexed.hpp>
#include <armnnUtils/Permute.hpp>
-#include <backendsCommon/test/DataLayoutUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/DataLayoutUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/ResizeTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ResizeTestImpl.hpp
index ce7d419..bbbe861 100644
--- a/src/backends/backendsCommon/test/layerTests/ResizeTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ResizeTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.hpp
index 0df9ea7..33d965b 100644
--- a/src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.cpp
index d6c0314..3ebb523 100644
--- a/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.cpp
@@ -5,11 +5,11 @@
#include "ShapeTestImpl.hpp"
-#include <backendsCommon/test/DataTypeUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <DataTypeUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
template<typename T, std::size_t n>
LayerTestResult<int32_t, 1> ShapeTest(
diff --git a/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.hpp
index 85f7c0a..8b95aa5 100644
--- a/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/SinTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/SinTestImpl.hpp
index b04d75a..ee7bcb9 100644
--- a/src/backends/backendsCommon/test/layerTests/SinTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/SinTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/SliceTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/SliceTestImpl.cpp
index f3e2836..ddf216d 100644
--- a/src/backends/backendsCommon/test/layerTests/SliceTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/SliceTestImpl.cpp
@@ -9,10 +9,10 @@
#include <ResolveType.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/SliceTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/SliceTestImpl.hpp
index d308268..c4d62cc 100644
--- a/src/backends/backendsCommon/test/layerTests/SliceTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/SliceTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp
index 375bdaa..05c4784 100644
--- a/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp
@@ -11,10 +11,10 @@
#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <algorithm>
diff --git a/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.hpp
index f0efe4d..9f93c02 100644
--- a/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/SpaceToBatchNdTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/SpaceToBatchNdTestImpl.cpp
index 44a37f4..69f5f5a 100644
--- a/src/backends/backendsCommon/test/layerTests/SpaceToBatchNdTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/SpaceToBatchNdTestImpl.cpp
@@ -11,10 +11,10 @@
#include <armnnUtils/Permute.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/SpaceToBatchNdTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/SpaceToBatchNdTestImpl.hpp
index 69ee99b..1f446b7 100644
--- a/src/backends/backendsCommon/test/layerTests/SpaceToBatchNdTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/SpaceToBatchNdTestImpl.hpp
@@ -4,7 +4,7 @@
//
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/SpaceToDepthTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/SpaceToDepthTestImpl.cpp
index 9175aec..d8c5747 100644
--- a/src/backends/backendsCommon/test/layerTests/SpaceToDepthTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/SpaceToDepthTestImpl.cpp
@@ -11,10 +11,10 @@
#include <armnnUtils/Permute.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/SpaceToDepthTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/SpaceToDepthTestImpl.hpp
index 29f2646..5a3e493 100644
--- a/src/backends/backendsCommon/test/layerTests/SpaceToDepthTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/SpaceToDepthTestImpl.hpp
@@ -4,7 +4,7 @@
//
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/SplitterTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/SplitterTestImpl.cpp
index e19a321..bf95a9f 100644
--- a/src/backends/backendsCommon/test/layerTests/SplitterTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/SplitterTestImpl.cpp
@@ -9,10 +9,10 @@
#include <ResolveType.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/SplitterTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/SplitterTestImpl.hpp
index 4007200..dc76bc9 100644
--- a/src/backends/backendsCommon/test/layerTests/SplitterTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/SplitterTestImpl.hpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/StackTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/StackTestImpl.cpp
index 25989f9..2a0e049 100644
--- a/src/backends/backendsCommon/test/layerTests/StackTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/StackTestImpl.cpp
@@ -4,7 +4,7 @@
//
#include "StackTestImpl.hpp"
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
@@ -12,10 +12,10 @@
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/StackTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/StackTestImpl.hpp
index 75e9ae8..24e88c4 100644
--- a/src/backends/backendsCommon/test/layerTests/StackTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/StackTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/StridedSliceTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/StridedSliceTestImpl.cpp
index af4b089..72ba681 100644
--- a/src/backends/backendsCommon/test/layerTests/StridedSliceTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/StridedSliceTestImpl.cpp
@@ -9,10 +9,10 @@
#include <ResolveType.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
namespace
{
diff --git a/src/backends/backendsCommon/test/layerTests/StridedSliceTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/StridedSliceTestImpl.hpp
index 52feb0c..3806d33 100644
--- a/src/backends/backendsCommon/test/layerTests/StridedSliceTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/StridedSliceTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/SubtractionTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/SubtractionTestImpl.hpp
index 6113b02..eba0d0a 100644
--- a/src/backends/backendsCommon/test/layerTests/SubtractionTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/SubtractionTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <Half.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp
index dae7483..34abc86 100644
--- a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp
@@ -12,13 +12,13 @@
#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/test/DataLayoutUtils.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/DataLayoutUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
#include <reference/RefWorkloadFactory.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp
index 0c45b0f..6af9e32 100644
--- a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/TransposeTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/TransposeTestImpl.hpp
index 6be8bcb..dceb386 100644
--- a/src/backends/backendsCommon/test/layerTests/TransposeTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/TransposeTestImpl.hpp
@@ -12,9 +12,9 @@
#include <backendsCommon/WorkloadFactory.hpp>
#include <backendsCommon/test/WorkloadFactoryHelper.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <WorkloadTestUtils.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
template<typename T>
LayerTestResult<T, 4> SimpleTransposeTestImpl(
diff --git a/src/backends/backendsCommon/test/layerTests/UnidirectionalSequenceLstmTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/UnidirectionalSequenceLstmTestImpl.cpp
index d17dceb..5315dd3 100644
--- a/src/backends/backendsCommon/test/layerTests/UnidirectionalSequenceLstmTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/UnidirectionalSequenceLstmTestImpl.cpp
@@ -9,8 +9,8 @@
#include <backendsCommon/TensorHandle.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
#include <ResolveType.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/UnidirectionalSequenceLstmTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/UnidirectionalSequenceLstmTestImpl.hpp
index 20ac313..88b09b9 100644
--- a/src/backends/backendsCommon/test/layerTests/UnidirectionalSequenceLstmTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/UnidirectionalSequenceLstmTestImpl.hpp
@@ -5,7 +5,7 @@
#pragma once
-#include "LayerTestResult.hpp"
+#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/cl/test/CMakeLists.txt b/src/backends/cl/test/CMakeLists.txt
index 8ee532a..af116a4 100644
--- a/src/backends/cl/test/CMakeLists.txt
+++ b/src/backends/cl/test/CMakeLists.txt
@@ -37,6 +37,7 @@
add_library(armnnClBackendUnitTests OBJECT ${armnnClBackendUnitTests_sources})
target_include_directories(armnnClBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnn)
target_include_directories(armnnClBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnnUtils)
+target_include_directories(armnnClBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnnTestUtils)
target_include_directories(armnnClBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/backends)
target_include_directories(armnnClBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/profiling)
target_include_directories(armnnClBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/profiling/common/include)
diff --git a/src/backends/cl/test/ClCreateWorkloadTests.cpp b/src/backends/cl/test/ClCreateWorkloadTests.cpp
index 4e40328..dd53f38 100644
--- a/src/backends/cl/test/ClCreateWorkloadTests.cpp
+++ b/src/backends/cl/test/ClCreateWorkloadTests.cpp
@@ -10,8 +10,8 @@
#include <armnn/utility/IgnoreUnused.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <backendsCommon/MemCopyWorkload.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
#include <aclCommon/test/CreateWorkloadClNeon.hpp>
#include <aclCommon/ArmComputeTensorUtils.hpp>
diff --git a/src/backends/cl/test/ClFallbackTests.cpp b/src/backends/cl/test/ClFallbackTests.cpp
index cfe2b36..6ac9433 100644
--- a/src/backends/cl/test/ClFallbackTests.cpp
+++ b/src/backends/cl/test/ClFallbackTests.cpp
@@ -3,9 +3,9 @@
// SPDX-License-Identifier: MIT
//
-#include <backendsCommon/test/CommonTestUtils.hpp>
+#include <CommonTestUtils.hpp>
-#include <test/GraphUtils.hpp>
+#include <GraphUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/cl/test/ClLayerSupportTests.cpp b/src/backends/cl/test/ClLayerSupportTests.cpp
index b18da11..1747cb6 100644
--- a/src/backends/cl/test/ClLayerSupportTests.cpp
+++ b/src/backends/cl/test/ClLayerSupportTests.cpp
@@ -8,7 +8,7 @@
#include <layers/ConvertFp16ToFp32Layer.hpp>
#include <layers/ConvertFp32ToFp16Layer.hpp>
#include <layers/MeanLayer.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <backendsCommon/TensorHandle.hpp>
#include <cl/ClWorkloadFactory.hpp>
diff --git a/src/backends/cl/test/ClLayerTests.cpp b/src/backends/cl/test/ClLayerTests.cpp
index 6c27d51..967a7e4 100644
--- a/src/backends/cl/test/ClLayerTests.cpp
+++ b/src/backends/cl/test/ClLayerTests.cpp
@@ -6,8 +6,8 @@
#include "ClContextControlFixture.hpp"
#include "ClWorkloadFactoryHelper.hpp"
-#include "test/TensorHelpers.hpp"
-#include "test/UnitTests.hpp"
+#include <TensorHelpers.hpp>
+#include <UnitTests.hpp>
#include <cl/ClLayerSupport.hpp>
#include <cl/ClWorkloadFactory.hpp>
diff --git a/src/backends/cl/test/ClOptimizedNetworkTests.cpp b/src/backends/cl/test/ClOptimizedNetworkTests.cpp
index 4c2a474..cf17eae 100644
--- a/src/backends/cl/test/ClOptimizedNetworkTests.cpp
+++ b/src/backends/cl/test/ClOptimizedNetworkTests.cpp
@@ -7,7 +7,7 @@
#include <Network.hpp>
-#include <test/GraphUtils.hpp>
+#include <GraphUtils.hpp>
#include <cl/ClWorkloadFactory.hpp>
#include <cl/ClBackendContext.hpp>
diff --git a/src/backends/cl/test/OpenClTimerTest.cpp b/src/backends/cl/test/OpenClTimerTest.cpp
index 0da1db7..85fdc81 100644
--- a/src/backends/cl/test/OpenClTimerTest.cpp
+++ b/src/backends/cl/test/OpenClTimerTest.cpp
@@ -7,7 +7,7 @@
#include "ClWorkloadFactoryHelper.hpp"
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
@@ -16,8 +16,8 @@
#include <cl/ClWorkloadFactory.hpp>
#include <cl/OpenClTimer.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
#include <arm_compute/runtime/CL/CLScheduler.h>
diff --git a/src/backends/neon/test/CMakeLists.txt b/src/backends/neon/test/CMakeLists.txt
index 9a45b7d..e4c5b34 100644
--- a/src/backends/neon/test/CMakeLists.txt
+++ b/src/backends/neon/test/CMakeLists.txt
@@ -53,6 +53,7 @@
add_library(armnnNeonBackendUnitTests OBJECT ${armnnNeonBackendUnitTests_sources})
target_include_directories(armnnNeonBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnn)
target_include_directories(armnnNeonBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnnUtils)
+target_include_directories(armnnNeonBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnnTestUtils)
target_include_directories(armnnNeonBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/backends)
target_include_directories(armnnNeonBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/profiling)
target_include_directories(armnnNeonBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/profiling/common/include)
diff --git a/src/backends/neon/test/NeonFallbackTests.cpp b/src/backends/neon/test/NeonFallbackTests.cpp
index ae6cfae..d2de843 100644
--- a/src/backends/neon/test/NeonFallbackTests.cpp
+++ b/src/backends/neon/test/NeonFallbackTests.cpp
@@ -3,10 +3,10 @@
// SPDX-License-Identifier: MIT
//
-#include <backendsCommon/test/CommonTestUtils.hpp>
+#include <CommonTestUtils.hpp>
#include <backendsCommon/test/mockBackend/MockImportBackend.hpp>
-#include <test/GraphUtils.hpp>
+#include <GraphUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/neon/test/NeonLayerSupportTests.cpp b/src/backends/neon/test/NeonLayerSupportTests.cpp
index 494c8f9..fbb91a9 100644
--- a/src/backends/neon/test/NeonLayerSupportTests.cpp
+++ b/src/backends/neon/test/NeonLayerSupportTests.cpp
@@ -7,7 +7,7 @@
#include <layers/ConvertFp16ToFp32Layer.hpp>
#include <layers/ConvertFp32ToFp16Layer.hpp>
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <backendsCommon/TensorHandle.hpp>
#include <neon/NeonWorkloadFactory.hpp>
diff --git a/src/backends/neon/test/NeonLayerTests.cpp b/src/backends/neon/test/NeonLayerTests.cpp
index 1750f24..3b63a88 100644
--- a/src/backends/neon/test/NeonLayerTests.cpp
+++ b/src/backends/neon/test/NeonLayerTests.cpp
@@ -5,8 +5,8 @@
#include "NeonWorkloadFactoryHelper.hpp"
-#include <test/TensorHelpers.hpp>
-#include <test/UnitTests.hpp>
+#include <TensorHelpers.hpp>
+#include <UnitTests.hpp>
#include <neon/NeonLayerSupport.hpp>
#include <neon/NeonWorkloadFactory.hpp>
diff --git a/src/backends/neon/test/NeonLayerTests_NDK_Bug.cpp b/src/backends/neon/test/NeonLayerTests_NDK_Bug.cpp
index 5a65b15..2410960 100644
--- a/src/backends/neon/test/NeonLayerTests_NDK_Bug.cpp
+++ b/src/backends/neon/test/NeonLayerTests_NDK_Bug.cpp
@@ -5,8 +5,9 @@
#include "NeonWorkloadFactoryHelper.hpp"
+#include <UnitTests.hpp>
+#include <backendsCommon/test/LayerTests.hpp>
#include <neon/NeonWorkloadFactory.hpp>
-#include <test/UnitTests.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/neon/test/NeonTensorHandleTests.cpp b/src/backends/neon/test/NeonTensorHandleTests.cpp
index 685a074..9d69a5c 100644
--- a/src/backends/neon/test/NeonTensorHandleTests.cpp
+++ b/src/backends/neon/test/NeonTensorHandleTests.cpp
@@ -11,9 +11,9 @@
#include <armnn/utility/NumericCast.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
-#include <test/GraphUtils.hpp>
+#include <GraphUtils.hpp>
#include <arm_compute/runtime/Allocator.h>
-#include <backendsCommon/test/CommonTestUtils.hpp>
+#include <CommonTestUtils.hpp>
#include <doctest/doctest.h>
#include <armnn/utility/Assert.hpp>
diff --git a/src/backends/neon/test/NeonTimerTest.cpp b/src/backends/neon/test/NeonTimerTest.cpp
index 87e1567..3596dfa 100644
--- a/src/backends/neon/test/NeonTimerTest.cpp
+++ b/src/backends/neon/test/NeonTimerTest.cpp
@@ -6,7 +6,7 @@
#include "NeonWorkloadFactoryHelper.hpp"
-#include <test/TensorHelpers.hpp>
+#include <TensorHelpers.hpp>
#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
@@ -15,8 +15,8 @@
#include <neon/NeonWorkloadFactory.hpp>
#include <backendsCommon/test/LayerTests.hpp>
-#include <backendsCommon/test/TensorCopyUtils.hpp>
-#include <backendsCommon/test/WorkloadTestUtils.hpp>
+#include <armnnTestUtils/TensorCopyUtils.hpp>
+#include <WorkloadTestUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/reference/test/CMakeLists.txt b/src/backends/reference/test/CMakeLists.txt
index d7c5da8..d5ce355 100644
--- a/src/backends/reference/test/CMakeLists.txt
+++ b/src/backends/reference/test/CMakeLists.txt
@@ -23,6 +23,7 @@
add_library(armnnRefBackendUnitTests OBJECT ${armnnRefBackendUnitTests_sources})
target_include_directories(armnnRefBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnn)
target_include_directories(armnnRefBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnnUtils)
+target_include_directories(armnnRefBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/armnnTestUtils)
target_include_directories(armnnRefBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/backends)
target_include_directories(armnnRefBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/src/profiling)
target_include_directories(armnnRefBackendUnitTests PRIVATE ${PROJECT_SOURCE_DIR}/profiling/common/include)
diff --git a/src/backends/reference/test/RefCreateWorkloadTests.cpp b/src/backends/reference/test/RefCreateWorkloadTests.cpp
index fae8d0c..e865f25 100644
--- a/src/backends/reference/test/RefCreateWorkloadTests.cpp
+++ b/src/backends/reference/test/RefCreateWorkloadTests.cpp
@@ -3,7 +3,7 @@
// SPDX-License-Identifier: MIT
//
-#include <test/CreateWorkload.hpp>
+#include <CreateWorkload.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <reference/RefTensorHandle.hpp>
diff --git a/src/backends/reference/test/RefLayerSupportTests.cpp b/src/backends/reference/test/RefLayerSupportTests.cpp
index 1adc54e..f0eb62f 100644
--- a/src/backends/reference/test/RefLayerSupportTests.cpp
+++ b/src/backends/reference/test/RefLayerSupportTests.cpp
@@ -5,7 +5,8 @@
#include <layers/ConvertFp16ToFp32Layer.hpp>
#include <layers/ConvertFp32ToFp16Layer.hpp>
-#include <test/TensorHelpers.hpp>
+
+#include <TensorHelpers.hpp>
#include <backendsCommon/TensorHandle.hpp>
#include <reference/RefWorkloadFactory.hpp>
diff --git a/src/backends/reference/test/RefLayerTests.cpp b/src/backends/reference/test/RefLayerTests.cpp
index 13487dd..9f5814b 100644
--- a/src/backends/reference/test/RefLayerTests.cpp
+++ b/src/backends/reference/test/RefLayerTests.cpp
@@ -9,7 +9,7 @@
#include <reference/RefWorkloadFactory.hpp>
-#include <test/UnitTests.hpp>
+#include <UnitTests.hpp>
TEST_SUITE("Compute_Reference")
{
diff --git a/src/backends/reference/test/RefOptimizedNetworkTests.cpp b/src/backends/reference/test/RefOptimizedNetworkTests.cpp
index 578d667..5b128a1 100644
--- a/src/backends/reference/test/RefOptimizedNetworkTests.cpp
+++ b/src/backends/reference/test/RefOptimizedNetworkTests.cpp
@@ -7,7 +7,7 @@
#include <Network.hpp>
#include <reference/RefWorkloadFactory.hpp>
-#include <test/GraphUtils.hpp>
+#include <GraphUtils.hpp>
#include <doctest/doctest.h>
diff --git a/src/backends/reference/workloads/RefChannelShuffleWorkload.cpp b/src/backends/reference/workloads/RefChannelShuffleWorkload.cpp
index 6571715..9f8514d 100644
--- a/src/backends/reference/workloads/RefChannelShuffleWorkload.cpp
+++ b/src/backends/reference/workloads/RefChannelShuffleWorkload.cpp
@@ -3,7 +3,6 @@
// SPDX-License-Identifier: MIT
//
-#include <backendsCommon/test/DataTypeUtils.hpp>
#include <armnn/backends/ITensorHandleFactory.hpp>
#include <armnnUtils/Transpose.hpp>
#include "RefChannelShuffleWorkload.hpp"
diff --git a/src/profiling/test/ProfilingTestUtils.cpp b/src/profiling/test/ProfilingTestUtils.cpp
index e0d3dd7..51f27d4 100644
--- a/src/profiling/test/ProfilingTestUtils.cpp
+++ b/src/profiling/test/ProfilingTestUtils.cpp
@@ -16,7 +16,7 @@
#include <common/include/LabelsAndEventClasses.hpp>
-#include <test/TestUtils.hpp>
+#include <TestUtils.hpp>
#include <doctest/doctest.h>