3 files changed, 79 insertions, 7 deletions

diff --git a/src/backends/gpuFsa/test/GpuFsaEndToEndTests.cpp b/src/backends/gpuFsa/test/GpuFsaEndToEndTests.cpp
index da6431f857..06b2a71dee 100644
--- a/src/backends/gpuFsa/test/GpuFsaEndToEndTests.cpp
+++ b/src/backends/gpuFsa/test/GpuFsaEndToEndTests.cpp
@@ -5,6 +5,7 @@
 
 #include "backendsCommon/test/EndToEndTestImpl.hpp"
 
+#include "backendsCommon/test/ActivationEndToEndTestImpl.hpp"
 #include "backendsCommon/test/BatchMatMulEndToEndTestImpl.hpp"
 #include "backendsCommon/test/Convolution2dEndToEndTestImpl.hpp"
 #include "backendsCommon/test/layerTests/CastTestImpl.hpp"
@@ -21,6 +22,18 @@ TEST_SUITE("GpuFsaEndToEnd")
 
 std::vector<BackendId> gpuFsaDefaultBackends = {"GpuFsa"};
 
+// Activation
+// TanH
+TEST_CASE("GpuFsaTanHEndToEndTestFloat32")
+{
+    ActivationEndToEndTest<DataType::Float32>(gpuFsaDefaultBackends, ActivationFunction::TanH, 1.f, 0, 1.f, 1.f);
+}
+// Sigmoid
+TEST_CASE("GpuFsaSigmoidEndToEndTestFloat32")
+{
+    ActivationEndToEndTest<DataType::Float32>(gpuFsaDefaultBackends, ActivationFunction::Sigmoid);
+}
+
 // BatchMatMul
 TEST_CASE("RefBatchMatMulEndToEndFloat32Test")
 {
diff --git a/src/backends/gpuFsa/test/GpuFsaLayerSupportTests.cpp b/src/backends/gpuFsa/test/GpuFsaLayerSupportTests.cpp
index cb1ddd8182..cf465c28ff 100644
--- a/src/backends/gpuFsa/test/GpuFsaLayerSupportTests.cpp
+++ b/src/backends/gpuFsa/test/GpuFsaLayerSupportTests.cpp
@@ -17,6 +17,24 @@ using namespace armnn;
 TEST_SUITE("GpuFsaLayerSupport")
 {
 
+TEST_CASE("IsLayerSupportedGpuFsaActivation")
+{
+    TensorInfo inputInfo ({ 1, 5, 5, 1 }, DataType::Float32);
+    TensorInfo outputInfo({ 1, 5, 5, 1 }, DataType::Float32);
+
+    ActivationDescriptor desc{};
+
+    GpuFsaLayerSupport supportChecker;
+    std::string reasonIfNotSupported;
+    auto supported = supportChecker.IsLayerSupported(LayerType::Activation,
+                                                     {inputInfo, outputInfo},
+                                                     desc,
+                                                     EmptyOptional(),
+                                                     EmptyOptional(),
+                                                     reasonIfNotSupported);
+    CHECK(supported);
+}
+
 TEST_CASE("IsLayerSupportedGpuFsaBatchMatMul")
 {
     TensorInfo input0Info({ 2, 2 }, DataType::Float32);
@@ -82,7 +100,6 @@ TEST_CASE("IsLayerSupportedGpuFsaConv2dUnsupported")
     TensorInfo outputInfo({ 1, 3, 3, 1 }, DataType::Float32);
     TensorInfo weightsInfo({ 1, 3, 3, 1 }, DataType::Float32, 0.0f, 0, true);
 
-    // NCHW is unsupported.
     Convolution2dDescriptor desc;
     desc.m_DataLayout = DataLayout::NCHW;
 
diff --git a/src/backends/gpuFsa/test/GpuFsaOptimizedNetworkTests.cpp b/src/backends/gpuFsa/test/GpuFsaOptimizedNetworkTests.cpp
index 1e5c976c00..ac341c2476 100644
--- a/src/backends/gpuFsa/test/GpuFsaOptimizedNetworkTests.cpp
+++ b/src/backends/gpuFsa/test/GpuFsaOptimizedNetworkTests.cpp
@@ -15,10 +15,56 @@ using namespace armnn;
 TEST_SUITE("GpuFsaOptimizedNetwork")
 {
 
-TEST_CASE("BatchMatMulSupportedOptimizedNetwork")
+TEST_CASE("ActivationSupportedOptimizedNetwork")
 {
-    using namespace armnn;
+    const float qScale = 1.0f;
+    const int32_t qOffset = 0;
+
+    const TensorShape& inputShape  = { 2, 2, 2 };
+    const TensorShape& outputShape  = { 2, 2, 2 };
+
+    TensorInfo inputTensorInfo(inputShape, DataType::Float32, qScale, qOffset, true);
+    TensorInfo outputTensorInfo(outputShape, DataType::Float32, qScale, qOffset);
+
+    IRuntime::CreationOptions options;
+    IRuntimePtr runtime(IRuntime::Create(options));
+    INetworkPtr network(INetwork::Create());
+
+    ActivationDescriptor desc;
+    SUBCASE("TanH")
+    {
+        desc.m_Function = ActivationFunction::TanH;
+        desc.m_A = 1.f;
+        desc.m_B = 1.f;
+    }
+    SUBCASE("Sigmoid")
+    {
+        desc.m_Function = ActivationFunction::Sigmoid;
+    }
+
+    IConnectableLayer* input = network->AddInputLayer(0, "input");
+    IConnectableLayer* activationLayer = network->AddActivationLayer(desc, "activation");
+    IConnectableLayer* output = network->AddOutputLayer(1, "output");
+
+    Connect(input, activationLayer, inputTensorInfo, 0, 0);
+    Connect(activationLayer, output, outputTensorInfo, 0, 0);
 
+    std::vector<BackendId> backends = { "GpuFsa" };
+
+    OptimizerOptionsOpaque 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<PreCompiledLayer>,
+                        &IsLayerOfType<OutputLayer>));
+}
+TEST_CASE("BatchMatMulSupportedOptimizedNetwork")
+{
     const float qScale = 1.0f;
     const int32_t qOffset = 0;
 
@@ -63,8 +109,6 @@ TEST_CASE("BatchMatMulSupportedOptimizedNetwork")
 
 TEST_CASE("CastSupportedOptimizedNetwork")
 {
-    using namespace armnn;
-
     const float qScale = 1.0f;
     const int32_t qOffset = 0;
 
@@ -221,8 +265,6 @@ TEST_CASE("TwoConv2dSupportedOptimizedNetwork")
 
 TEST_CASE("ElementwiseBinarySupportedOptimizedNetwork")
 {
-    using namespace armnn;
-
     const float qScale = 1.0f;
     const int32_t qOffset = 0;