1 files changed, 127 insertions, 1 deletions
diff --git a/src/backends/gpuFsa/test/GpuFsaOptimizedNetworkTests.cpp b/src/backends/gpuFsa/test/GpuFsaOptimizedNetworkTests.cpp
index fa97b135df..92521a0376 100644
--- a/src/backends/gpuFsa/test/GpuFsaOptimizedNetworkTests.cpp
+++ b/src/backends/gpuFsa/test/GpuFsaOptimizedNetworkTests.cpp
@@ -8,4 +8,130 @@
 #include <GraphUtils.hpp>
 #include <TestUtils.hpp>
 
-#include <doctest/doctest.h>
-\ No newline at end of file
+#include <doctest/doctest.h>
+
+using namespace armnn;
+
+TEST_SUITE("GpuFsaOptimizedNetwork")
+{
+
+TEST_CASE("SingleConv2dSupportedOptimizedNetwork")
+{
+    IRuntime::CreationOptions options;
+    IRuntimePtr runtime(IRuntime::Create(options));
+    INetworkPtr network(INetwork::Create());
+
+    TensorInfo inputInfo({ 1, 5, 5, 1 }, DataType::Float32);
+    TensorInfo outputInfo({ 1, 3, 3, 1 }, DataType::Float32);
+    TensorInfo weightsInfo({ 1, 3, 3, 1 }, DataType::Float32, 0.0f, 0, true);
+    TensorInfo biasesInfo({ 1 }, DataType::Float32, 0.0f, 0, true);
+
+    Convolution2dDescriptor desc;
+    desc.m_BiasEnabled = true;
+    desc.m_DataLayout = DataLayout::NHWC;
+
+    auto inputLayer = network->AddInputLayer(0, "input");
+    auto weightLayer = network->AddConstantLayer(ConstTensor(weightsInfo, nullptr), "weights");
+    auto biasLayer = network->AddConstantLayer(ConstTensor(biasesInfo, nullptr), "bias");
+    auto convLayer = network->AddConvolution2dLayer(desc, "conv2d");
+    auto outputLayer = network->AddOutputLayer(1, "output");
+
+    inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0));
+    inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+
+    weightLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(1));
+    weightLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo);
+
+    biasLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(2));
+    biasLayer->GetOutputSlot(0).SetTensorInfo(biasesInfo);
+
+    convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+    convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+    std::vector<BackendId> backends = { "GpuFsa" };
+
+    OptimizerOptions optimizedOptions;
+    IOptimizedNetworkPtr optNet = Optimize(*network, backends, runtime->GetDeviceSpec(), optimizedOptions);
+    CHECK(optNet);
+
+    Graph& graph = GetGraphForTesting(optNet.get());
+
+    // Check graph layer sequence to ensure that the network has been replaced with a PreCompiledLayer
+    CHECK(CheckSequence(graph.cbegin(), graph.cend(),
+                        &IsLayerOfType<InputLayer>,
+                        &IsLayerOfType<ConstantLayer>,
+                        &IsLayerOfType<ConstantLayer>,
+                        &IsLayerOfType<PreCompiledLayer>,
+                        &IsLayerOfType<OutputLayer>));
+}
+
+TEST_CASE("TwoConv2dSupportedOptimizedNetwork")
+{
+    IRuntime::CreationOptions options;
+    IRuntimePtr runtime(IRuntime::Create(options));
+    INetworkPtr network(INetwork::Create());
+
+    TensorInfo inputInfo({ 1, 5, 5, 1 }, DataType::Float32);
+    TensorInfo intermediateInfo({ 1, 3, 3, 1 }, DataType::Float32);
+    TensorInfo outputInfo({ 1, 1, 1, 1 }, DataType::Float32);
+    TensorInfo weightsInfo({ 1, 3, 3, 1 }, DataType::Float32, 0.0f, 0, true);
+    TensorInfo biasesInfo({ 1 }, DataType::Float32, 0.0f, 0, true);
+
+    Convolution2dDescriptor desc;
+    desc.m_BiasEnabled = true;
+    desc.m_DataLayout = DataLayout::NHWC;
+
+    auto inputLayer = network->AddInputLayer(0, "input");
+
+    auto weightLayer1 = network->AddConstantLayer(ConstTensor(weightsInfo, nullptr), "weights");
+    auto biasLayer1 = network->AddConstantLayer(ConstTensor(biasesInfo, nullptr), "bias");
+    auto convLayer1 = network->AddConvolution2dLayer(desc, "conv2d");
+
+    auto weightLayer2 = network->AddConstantLayer(ConstTensor(weightsInfo, nullptr), "weights");
+    auto biasLayer2 = network->AddConstantLayer(ConstTensor(biasesInfo, nullptr), "bias");
+    auto convLayer2 = network->AddConvolution2dLayer(desc, "conv2d");
+
+    auto outputLayer = network->AddOutputLayer(0, "output");
+
+    inputLayer->GetOutputSlot(0).Connect(convLayer1->GetInputSlot(0));
+    inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+
+    weightLayer1->GetOutputSlot(0).Connect(convLayer1->GetInputSlot(1));
+    weightLayer1->GetOutputSlot(0).SetTensorInfo(weightsInfo);
+
+    biasLayer1->GetOutputSlot(0).Connect(convLayer1->GetInputSlot(2));
+    biasLayer1->GetOutputSlot(0).SetTensorInfo(biasesInfo);
+
+    convLayer1->GetOutputSlot(0).Connect(convLayer2->GetInputSlot(0));
+    convLayer1->GetOutputSlot(0).SetTensorInfo(intermediateInfo);
+
+    weightLayer2->GetOutputSlot(0).Connect(convLayer2->GetInputSlot(1));
+    weightLayer2->GetOutputSlot(0).SetTensorInfo(weightsInfo);
+
+    biasLayer2->GetOutputSlot(0).Connect(convLayer2->GetInputSlot(2));
+    biasLayer2->GetOutputSlot(0).SetTensorInfo(biasesInfo);
+
+    convLayer2->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+    convLayer2->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+    std::vector<BackendId> backends = { "GpuFsa" };
+
+    OptimizerOptions optimizedOptions;
+    IOptimizedNetworkPtr optNet = Optimize(*network, backends, runtime->GetDeviceSpec(), optimizedOptions);
+    CHECK(optNet);
+
+    Graph& graph = GetGraphForTesting(optNet.get());
+
+    // Check graph layer sequence to ensure that the network has been replaced with a PreCompiledLayer
+    CHECK(CheckSequence(graph.cbegin(), graph.cend(),
+                        &IsLayerOfType<InputLayer>,
+                        &IsLayerOfType<ConstantLayer>,
+                        &IsLayerOfType<ConstantLayer>,
+                        &IsLayerOfType<ConstantLayer>,
+                        &IsLayerOfType<ConstantLayer>,
+                        &IsLayerOfType<PreCompiledLayer>,
+                        &IsLayerOfType<PreCompiledLayer>,
+                        &IsLayerOfType<OutputLayer>));
+}
+
+}
+\ No newline at end of file