IVGCVSW-2073: Move remaining backend-specific tests from armnn to backends
Change-Id: I45fd5b6dd32c435b78a54dc377a623e60978ce13
diff --git a/src/backends/test/EndToEndTestImpl.hpp b/src/backends/test/EndToEndTestImpl.hpp
new file mode 100644
index 0000000..5f17f78
--- /dev/null
+++ b/src/backends/test/EndToEndTestImpl.hpp
@@ -0,0 +1,102 @@
+//
+// 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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