diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp
index 66e30f0..ca9d7d9 100644
--- a/src/backends/backendsCommon/WorkloadData.cpp
+++ b/src/backends/backendsCommon/WorkloadData.cpp
@@ -301,7 +301,8 @@
     std::vector<DataType> supportedTypes = {
         DataType::Float32,
         DataType::Float16,
-        DataType::QuantisedAsymm8
+        DataType::QuantisedAsymm8,
+        DataType::QuantisedSymm16
     };
 
     ValidateDataTypes(workloadInfo.m_InputTensorInfos[0],
diff --git a/src/backends/backendsCommon/test/ActivationTestImpl.hpp b/src/backends/backendsCommon/test/ActivationTestImpl.hpp
index ca61302..1a5bcd4 100644
--- a/src/backends/backendsCommon/test/ActivationTestImpl.hpp
+++ b/src/backends/backendsCommon/test/ActivationTestImpl.hpp
@@ -377,6 +377,14 @@
         workloadFactory, memoryManager, 4.0f, 3);
 }
 
+LayerTestResult<int16_t, 4> ConstantLinearActivationInt16Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return ConstantLinearActivationTestCommon<armnn::DataType::QuantisedSymm16>(
+            workloadFactory, memoryManager, 0.1f, 0);
+}
+
 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
 LayerTestResult<T, 4> SimpleActivationTest(
     armnn::IWorkloadFactory& workloadFactory,
@@ -492,6 +500,342 @@
     return SimpleSigmoidTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.1f, 50);
 }
 
+LayerTestResult<int16_t, 4> SimpleSigmoidInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return SimpleSigmoidTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> ReLuTestCommon(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        float qScale,
+        int32_t qOffset)
+{
+    std::vector<float> inputData = {
+            -0.1f, -0.2f, -0.3f, -0.4f,
+            0.1f,  0.2f,  0.3f,  0.4f,
+            -1.0f, -2.0f, -3.0f, -4.0f,
+            1.0f,  2.0f,  3.0f,  4.0f
+    };
+
+    // Calculate output values for input.
+    auto f = [](float value)
+    {
+        return std::fmax(0.0f, value);
+    };
+    std::vector<float> outputExpectedData(inputData.size());
+    std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+    return SimpleActivationTest<ArmnnType>(workloadFactory,
+                                           memoryManager,
+                                           armnn::ActivationFunction::ReLu,
+                                           0.f,
+                                           0.f,
+                                           qScale,
+                                           qOffset,
+                                           inputData,
+                                           outputExpectedData);
+}
+
+LayerTestResult<int16_t, 4> ReLuInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return ReLuTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0);
+}
+
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> BoundedReLuTestCommon(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        float qScale,
+        int32_t qOffset)
+{
+    std::vector<float> inputData = {
+            -0.1f, -0.2f, -0.3f, -0.4f,
+            0.1f,  0.2f,  0.3f,  0.4f,
+            -1.0f, -2.0f, -3.0f, -4.0f,
+            1.0f,  2.0f,  3.0f,  4.0f
+    };
+    const float a = 1.0f;
+    const float b = -1.0f;
+    // Calculate output values for input.
+    auto f = [a, b](float value)
+    {
+        return std::min(a, std::max(b, value));
+    };
+    std::vector<float> outputExpectedData(inputData.size());
+    std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+    return SimpleActivationTest<ArmnnType>(workloadFactory,
+                                           memoryManager,
+                                           armnn::ActivationFunction::BoundedReLu,
+                                           a,
+                                           b,
+                                           qScale,
+                                           qOffset,
+                                           inputData,
+                                           outputExpectedData);
+}
+
+LayerTestResult<int16_t, 4> BoundedReLuInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return ReLuTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0);
+}
+
+
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> SoftReLuTestCommon(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        float qScale,
+        int32_t qOffset)
+{
+    std::vector<float> inputData = {
+            -0.1f, -0.2f, -0.3f, -0.4f,
+            0.1f,  0.2f,  0.3f,  0.4f,
+            -1.0f, -2.0f, -3.0f, -4.0f,
+            1.0f,  2.0f,  3.0f,  4.0f
+    };
+
+    // Calculate output values for input.
+    auto f = [](float value)
+    {
+        return std::log(1.0f + std::exp(value));
+    };
+    std::vector<float> outputExpectedData(inputData.size());
+    std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+    return SimpleActivationTest<ArmnnType>(workloadFactory,
+                                           memoryManager,
+                                           armnn::ActivationFunction::SoftReLu,
+                                           0.f,
+                                           0.f,
+                                           qScale,
+                                           qOffset,
+                                           inputData,
+                                           outputExpectedData);
+}
+
+LayerTestResult<int16_t, 4> SoftReLuInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return SoftReLuTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> LeakyReLuTestCommon(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        float qScale,
+        int32_t qOffset)
+{
+    std::vector<float> inputData = {
+            -0.1f, -0.2f, -0.3f, -0.4f,
+            0.1f,  0.2f,  0.3f,  0.4f,
+            -1.0f, -2.0f, -3.0f, -4.0f,
+            1.0f,  2.0f,  3.0f,  4.0f
+    };
+
+    const float a = 0.01f;
+    // Calculate output values for input.
+    auto f = [a](float value)
+    {
+        return value > 0.0f ? value : (value * a);
+    };
+    std::vector<float> outputExpectedData(inputData.size());
+    std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+    return SimpleActivationTest<ArmnnType>(workloadFactory,
+                                           memoryManager,
+                                           armnn::ActivationFunction::LeakyReLu,
+                                           a,
+                                           0.f,
+                                           qScale,
+                                           qOffset,
+                                           inputData,
+                                           outputExpectedData);
+}
+
+LayerTestResult<int16_t, 4> LeakyReLuInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return LeakyReLuTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> AbsTestCommon(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        float qScale,
+        int32_t qOffset)
+{
+    std::vector<float> inputData = {
+            -0.1f, -0.2f, -0.3f, -0.4f,
+            0.1f,  0.2f,  0.3f,  0.4f,
+            -1.0f, -2.0f, -3.0f, -4.0f,
+            1.0f,  2.0f,  3.0f,  4.0f
+    };
+
+    // Calculate output values for input.
+    auto f = [](float value)
+    {
+        return std::abs(value);
+    };
+    std::vector<float> outputExpectedData(inputData.size());
+    std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+    return SimpleActivationTest<ArmnnType>(workloadFactory,
+                                           memoryManager,
+                                           armnn::ActivationFunction::Abs,
+                                           0.f,
+                                           0.f,
+                                           qScale,
+                                           qOffset,
+                                           inputData,
+                                           outputExpectedData);
+}
+
+LayerTestResult<int16_t, 4> AbsInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return AbsTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> SqrtTestCommon(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        float qScale,
+        int32_t qOffset)
+{
+    std::vector<float> inputData = {
+            0.1f,  0.2f,  0.3f,  0.4f,
+            0.1f,  0.2f,  0.3f,  0.4f,
+            1.0f,  2.0f,  3.0f,  4.0f,
+            1.0f,  2.0f,  3.0f,  4.0f
+    };
+
+    // Calculate output values for input.
+    auto f = [](float value)
+    {
+        return std::sqrt(value);
+    };
+    std::vector<float> outputExpectedData(inputData.size());
+    std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+    return SimpleActivationTest<ArmnnType>(workloadFactory,
+                                           memoryManager,
+                                           armnn::ActivationFunction::Sqrt,
+                                           0.f,
+                                           0.f,
+                                           qScale,
+                                           qOffset,
+                                           inputData,
+                                           outputExpectedData);
+}
+
+LayerTestResult<int16_t, 4> SqrtInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return SqrtTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> SquareTestCommon(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        float qScale,
+        int32_t qOffset)
+{
+    std::vector<float> inputData = {
+            -0.1f, -0.2f, -0.3f, -0.4f,
+            0.1f,  0.2f,  0.3f,  0.4f,
+            -1.0f, -2.0f, -3.0f, -4.0f,
+            1.0f,  2.0f,  3.0f,  4.0f
+    };
+
+    // Calculate output values for input.
+    auto f = [](float value)
+    {
+        return std::pow(value,2);
+    };
+    std::vector<float> outputExpectedData(inputData.size());
+    std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+    return SimpleActivationTest<ArmnnType>(workloadFactory,
+                                           memoryManager,
+                                           armnn::ActivationFunction::Square,
+                                           0.f,
+                                           0.f,
+                                           qScale,
+                                           qOffset,
+                                           inputData,
+                                           outputExpectedData);
+}
+
+LayerTestResult<int16_t, 4> SquareInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return SquareTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> TanhTestCommon(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        float qScale,
+        int32_t qOffset)
+{
+    std::vector<float> inputData = {
+            -0.1f, -0.2f, -0.3f, -0.4f,
+            0.1f,  0.2f,  0.3f,  0.4f,
+            -1.0f, -2.0f, -3.0f, -4.0f,
+            1.0f,  2.0f,  3.0f,  4.0f
+    };
+
+    const float a = 2.0f;
+    const float b = 3.0f;
+    // Calculate output values for input.
+    auto f = [a, b](float value)
+    {
+        return a * tanhf(b * value);
+    };
+    std::vector<float> outputExpectedData(inputData.size());
+    std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+    return SimpleActivationTest<ArmnnType>(workloadFactory,
+                                           memoryManager,
+                                           armnn::ActivationFunction::TanH,
+                                           a,
+                                           b,
+                                           qScale,
+                                           qOffset,
+                                           inputData,
+                                           outputExpectedData);
+}
+
+LayerTestResult<int16_t, 4> TanhInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    return TanhTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0);
+}
+
+
+
 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
 LayerTestResult<T,4> CompareActivationTestImpl(
     armnn::IWorkloadFactory& workloadFactory,
@@ -606,3 +950,13 @@
     return CompareActivationTestImpl<armnn::DataType::QuantisedAsymm8>(
         workloadFactory, memoryManager, refWorkloadFactory, f, 5, 0.1f, 50);
 }
+
+LayerTestResult<int16_t,4> CompareActivationInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        armnn::IWorkloadFactory& refWorkloadFactory,
+        armnn::ActivationFunction f)
+{
+    return CompareActivationTestImpl<armnn::DataType::QuantisedSymm16>(
+            workloadFactory, memoryManager, refWorkloadFactory, f, 5, 0.1f, 0);
+}
diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp
index c748be1..762e581 100644
--- a/src/backends/backendsCommon/test/LayerTests.hpp
+++ b/src/backends/backendsCommon/test/LayerTests.hpp
@@ -494,6 +494,10 @@
     armnn::IWorkloadFactory& workloadFactory,
     const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
 
+LayerTestResult<int16_t, 4> SimpleSigmoidInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
 LayerTestResult<float, 4> CompareConvolution2dTest(
     armnn::IWorkloadFactory& workloadFactory,
     const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
@@ -642,6 +646,40 @@
     float upperBound,
     float lowerBound);
 
+
+LayerTestResult<int16_t, 4> ReLuInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+LayerTestResult<int16_t, 4> BoundedReLuInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+LayerTestResult<int16_t, 4> SoftReLuInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+LayerTestResult<int16_t, 4> LeakyReLuInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+LayerTestResult<int16_t, 4> AbsInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+LayerTestResult<int16_t, 4> SqrtInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+LayerTestResult<int16_t, 4> SquareInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+LayerTestResult<int16_t, 4> TanhInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+
 // Tests that the output should be identical to the input when the output dimensions match the input ones.
 LayerTestResult<float, 4> ResizeBilinearNopTest(
     armnn::IWorkloadFactory& workloadFactory,
@@ -823,6 +861,12 @@
     armnn::IWorkloadFactory& refWorkloadFactory,
     armnn::ActivationFunction f);
 
+LayerTestResult<int16_t, 4> CompareActivationInt16Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        armnn::IWorkloadFactory& refWorkloadFactory,
+        armnn::ActivationFunction f);
+
 LayerTestResult<uint8_t, 2> CompareSoftmaxUint8Test(
     armnn::IWorkloadFactory& workloadFactory,
     const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
@@ -905,6 +949,10 @@
     armnn::IWorkloadFactory& workloadFactory,
     const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
 
+LayerTestResult<int16_t, 4> ConstantLinearActivationInt16Test(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
 LayerTestResult<uint8_t, 4> ResizeBilinearNopUint8Test(
     armnn::IWorkloadFactory& workloadFactory,
     const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
diff --git a/src/backends/reference/RefLayerSupport.cpp b/src/backends/reference/RefLayerSupport.cpp
index 3512d52..1b1f0ce 100644
--- a/src/backends/reference/RefLayerSupport.cpp
+++ b/src/backends/reference/RefLayerSupport.cpp
@@ -167,9 +167,10 @@
    bool supported = true;
 
     // Define supported types.
-    std::array<DataType,2> supportedTypes = {
+    std::array<DataType,3> supportedTypes = {
         DataType::Float32,
-        DataType::QuantisedAsymm8
+        DataType::QuantisedAsymm8,
+        DataType::QuantisedSymm16
     };
 
     supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported,
diff --git a/src/backends/reference/test/RefLayerTests.cpp b/src/backends/reference/test/RefLayerTests.cpp
index cbc56d1..04b215a 100644
--- a/src/backends/reference/test/RefLayerTests.cpp
+++ b/src/backends/reference/test/RefLayerTests.cpp
@@ -167,9 +167,10 @@
 ARMNN_AUTO_TEST_CASE(AsymmNonSquarePooling2d, AsymmetricNonSquarePooling2dTest)
 ARMNN_AUTO_TEST_CASE(AsymmNonSquarePooling2dUint8, AsymmetricNonSquarePooling2dUint8Test)
 
-// Activation
+// Linear Activation
 ARMNN_AUTO_TEST_CASE(ConstantLinearActivation, ConstantLinearActivationTest)
 ARMNN_AUTO_TEST_CASE(ConstantLinearActivationUint8, ConstantLinearActivationUint8Test)
+ARMNN_AUTO_TEST_CASE(ConstantLinearActivationInt16, ConstantLinearActivationInt16Test)
 
 // Normalization
 ARMNN_AUTO_TEST_CASE(SimpleNormalizationAcross, SimpleNormalizationAcrossTest)
@@ -188,14 +189,39 @@
 ARMNN_AUTO_TEST_CASE(Simple4dSoftmax, Simple4dSoftmaxTest, 1.0f)
 ARMNN_AUTO_TEST_CASE(Simple4dSoftmaxUint8, Simple4dSoftmaxUint8Test, 1.0f)
 
-// Sigmoid
+// Sigmoid Activation
 ARMNN_AUTO_TEST_CASE(SimpleSigmoid, SimpleSigmoidTest)
 ARMNN_AUTO_TEST_CASE(SimpleSigmoidUint8, SimpleSigmoidUint8Test)
+ARMNN_AUTO_TEST_CASE(SimpleSigmoidInt16, SimpleSigmoidInt16Test)
 
+// BoundedReLU Activation
 ARMNN_AUTO_TEST_CASE(ReLu1, BoundedReLuUpperAndLowerBoundTest)
 ARMNN_AUTO_TEST_CASE(ReLu6, BoundedReLuUpperBoundOnlyTest)
 ARMNN_AUTO_TEST_CASE(ReLu1Uint8, BoundedReLuUint8UpperAndLowerBoundTest)
 ARMNN_AUTO_TEST_CASE(ReLu6Uint8, BoundedReLuUint8UpperBoundOnlyTest)
+ARMNN_AUTO_TEST_CASE(BoundedReLuInt16, BoundedReLuInt16Test)
+
+// ReLU Activation
+ARMNN_AUTO_TEST_CASE(ReLuInt16, ReLuInt16Test)
+
+// SoftReLU Activation
+ARMNN_AUTO_TEST_CASE(SoftReLuInt16, SoftReLuInt16Test)
+
+// LeakyReLU Activation
+ARMNN_AUTO_TEST_CASE(LeakyReLuInt16, LeakyReLuInt16Test)
+
+// Abs Activation
+ARMNN_AUTO_TEST_CASE(AbsInt16, AbsInt16Test)
+
+// Sqrt Activation
+ARMNN_AUTO_TEST_CASE(SqrtInt16, SqrtInt16Test)
+
+// Square Activation
+ARMNN_AUTO_TEST_CASE(SquareInt16, SquareInt16Test)
+
+// Tanh Activation
+ARMNN_AUTO_TEST_CASE(TanhInt16, TanhInt16Test)
+
 
 // Fully Conected
 ARMNN_AUTO_TEST_CASE(SimpleFullyConnected, FullyConnectedFloat32Test, false, false)