+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);
+}
+
+
+