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Diffstat (limited to 'src/backends/test/EndToEndTestImpl.hpp')
| -rw-r--r-- | src/backends/test/EndToEndTestImpl.hpp | 102 |
1 files changed, 0 insertions, 102 deletions
diff --git a/src/backends/test/EndToEndTestImpl.hpp b/src/backends/test/EndToEndTestImpl.hpp deleted file mode 100644 index 5f17f782f3..0000000000 --- a/src/backends/test/EndToEndTestImpl.hpp +++ /dev/null @@ -1,102 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// -#pragma once - -#include <armnn/ArmNN.hpp> - -#include <backends/test/QuantizeHelper.hpp> - -#include <vector> - -namespace -{ - -using namespace armnn; - -template<typename T> -bool ConstantUsageTest(const std::vector<BackendId>& computeDevice, - const TensorInfo& commonTensorInfo, - const std::vector<T>& inputData, - const std::vector<T>& constantData, - const std::vector<T>& expectedOutputData) -{ - // Create runtime in which test will run - IRuntime::CreationOptions options; - IRuntimePtr runtime(IRuntime::Create(options)); - - // Builds up the structure of the network. - INetworkPtr net(INetwork::Create()); - - IConnectableLayer* input = net->AddInputLayer(0); - IConnectableLayer* constant = net->AddConstantLayer(ConstTensor(commonTensorInfo, constantData)); - IConnectableLayer* add = net->AddAdditionLayer(); - IConnectableLayer* output = net->AddOutputLayer(0); - - input->GetOutputSlot(0).Connect(add->GetInputSlot(0)); - constant->GetOutputSlot(0).Connect(add->GetInputSlot(1)); - add->GetOutputSlot(0).Connect(output->GetInputSlot(0)); - - // Sets the tensors in the network. - input->GetOutputSlot(0).SetTensorInfo(commonTensorInfo); - constant->GetOutputSlot(0).SetTensorInfo(commonTensorInfo); - add->GetOutputSlot(0).SetTensorInfo(commonTensorInfo); - - // optimize the network - IOptimizedNetworkPtr optNet = Optimize(*net, computeDevice, runtime->GetDeviceSpec()); - - // Loads it into the runtime. - NetworkId netId; - runtime->LoadNetwork(netId, std::move(optNet)); - - // Creates structures for input & output. - std::vector<T> outputData(inputData.size()); - - InputTensors inputTensors - { - {0, ConstTensor(runtime->GetInputTensorInfo(netId, 0), inputData.data())} - }; - OutputTensors outputTensors - { - {0, Tensor(runtime->GetOutputTensorInfo(netId, 0), outputData.data())} - }; - - // Does the inference. - runtime->EnqueueWorkload(netId, inputTensors, outputTensors); - - // Checks the results. - return outputData == expectedOutputData; -} - -inline bool ConstantUsageFloat32Test(const std::vector<BackendId>& backends) -{ - const TensorInfo commonTensorInfo({ 2, 3 }, DataType::Float32); - - return ConstantUsageTest(backends, - commonTensorInfo, - std::vector<float>{ 1.f, 2.f, 3.f, 4.f, 5.f, 6.f }, // Input. - std::vector<float>{ 6.f, 5.f, 4.f, 3.f, 2.f, 1.f }, // Const input. - std::vector<float>{ 7.f, 7.f, 7.f, 7.f, 7.f, 7.f } // Expected output. - ); -} - -inline bool ConstantUsageUint8Test(const std::vector<BackendId>& backends) -{ - TensorInfo commonTensorInfo({ 2, 3 }, DataType::QuantisedAsymm8); - - const float scale = 0.023529f; - const int8_t offset = -43; - - commonTensorInfo.SetQuantizationScale(scale); - commonTensorInfo.SetQuantizationOffset(offset); - - return ConstantUsageTest(backends, - commonTensorInfo, - QuantizedVector<uint8_t>(scale, offset, { 1.f, 2.f, 3.f, 4.f, 5.f, 6.f }), // Input. - QuantizedVector<uint8_t>(scale, offset, { 6.f, 5.f, 4.f, 3.f, 2.f, 1.f }), // Const input. - QuantizedVector<uint8_t>(scale, offset, { 7.f, 7.f, 7.f, 7.f, 7.f, 7.f }) // Expected output. - ); -} - -} // anonymous namespace
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