IVGCVSW-7451 LEAKY_RELU not supported by delegate
* Added LEAKY_RELU support to classic and opaque delegate
* CMake files updated
* Test added
Signed-off-by: Tianle Cheng <tianle.cheng@arm.com>
Change-Id: Ib9a2ce8f637b14afcd796bbae11fd3fa03653a2c
diff --git a/delegate/classic/src/Activation.hpp b/delegate/classic/src/Activation.hpp
index e813956..442ce4f 100644
--- a/delegate/classic/src/Activation.hpp
+++ b/delegate/classic/src/Activation.hpp
@@ -101,6 +101,14 @@
activationDesc.m_Function = armnn::ActivationFunction::HardSwish;
break;
}
+ case kTfLiteBuiltinLeakyRelu:
+ {
+ // Get the alpha param from builtin data
+ auto* leakyReluParameters = reinterpret_cast<TfLiteLeakyReluParams*>(tfLiteNode->builtin_data);
+ activationDesc.m_Function = armnn::ActivationFunction::LeakyReLu;
+ activationDesc.m_A = leakyReluParameters->alpha;
+ break;
+ }
default:
{
return kTfLiteError;
diff --git a/delegate/classic/src/armnn_delegate.cpp b/delegate/classic/src/armnn_delegate.cpp
index 45bea3d..2483835 100644
--- a/delegate/classic/src/armnn_delegate.cpp
+++ b/delegate/classic/src/armnn_delegate.cpp
@@ -741,10 +741,16 @@
kTfLiteBuiltinL2Normalization);
case kTfLiteBuiltinL2Pool2d:
return VisitPooling2dOperator(delegateData,
- tfLiteContext,
- tfLiteNode,
- nodeIndex,
- kTfLiteBuiltinL2Pool2d);
+ tfLiteContext,
+ tfLiteNode,
+ nodeIndex,
+ kTfLiteBuiltinL2Pool2d);
+ case kTfLiteBuiltinLeakyRelu:
+ return VisitActivationOperator(delegateData,
+ tfLiteContext,
+ tfLiteNode,
+ nodeIndex,
+ kTfLiteBuiltinLeakyRelu);
case kTfLiteBuiltinLess:
return VisitComparisonOperator(delegateData,
tfLiteContext,
diff --git a/delegate/opaque/src/Activation.hpp b/delegate/opaque/src/Activation.hpp
index 9fce7a1..f566090 100644
--- a/delegate/opaque/src/Activation.hpp
+++ b/delegate/opaque/src/Activation.hpp
@@ -166,6 +166,15 @@
activationDesc.m_Function = armnn::ActivationFunction::HardSwish;
break;
}
+ case kTfLiteBuiltinLeakyRelu:
+ {
+ // Get alpha param from builtin data
+ auto* leakyReluParameters =
+ reinterpret_cast<TfLiteLeakyReluParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
+ activationDesc.m_Function = armnn::ActivationFunction::LeakyReLu;
+ activationDesc.m_A = leakyReluParameters->alpha;
+ break;
+ }
default:
{
return kTfLiteError;
diff --git a/delegate/opaque/src/armnn_delegate.cpp b/delegate/opaque/src/armnn_delegate.cpp
index 49fa30d..60da293 100644
--- a/delegate/opaque/src/armnn_delegate.cpp
+++ b/delegate/opaque/src/armnn_delegate.cpp
@@ -828,6 +828,12 @@
tfLiteNode,
nodeIndex,
kTfLiteBuiltinL2Pool2d);
+ case kTfLiteBuiltinLeakyRelu:
+ return VisitActivationOperator(delegateData,
+ tfLiteContext,
+ tfLiteNode,
+ nodeIndex,
+ kTfLiteBuiltinLeakyRelu);
case kTfLiteBuiltinLess:
return VisitComparisonOperator(delegateData,
tfLiteContext,
diff --git a/delegate/test/ActivationTest.cpp b/delegate/test/ActivationTest.cpp
index 8f2f198..620c299 100644
--- a/delegate/test/ActivationTest.cpp
+++ b/delegate/test/ActivationTest.cpp
@@ -170,6 +170,32 @@
outputExpectedData);
}
+void ActivationLeakyReLuTest(std::vector<armnn::BackendId>& backends)
+{
+ 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
+ };
+
+ float alpha = 0.3f;
+
+ // Calculate output values for input.
+ auto f = [alpha](float value)
+ {
+ return value > 0 ? value : value * alpha;
+ };
+ std::vector<float> outputExpectedData(inputData.size());
+ std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);
+
+ ActivationTest(tflite::BuiltinOperator_LEAKY_RELU,
+ backends,
+ inputData,
+ outputExpectedData,
+ alpha);
+}
+
TEST_SUITE("Activation_CpuRefTests")
{
@@ -209,6 +235,12 @@
ActivationHardSwishTest(backends);
}
+TEST_CASE ("Activation_LeakyRelu_CpuRef_Test")
+{
+ std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
+ ActivationLeakyReLuTest(backends);
+}
+
}
TEST_SUITE("Activation_CpuAccTests")
@@ -250,6 +282,12 @@
ActivationHardSwishTest(backends);
}
+TEST_CASE ("Activation_LeakyRelu_CpuAcc_Test")
+{
+ std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
+ ActivationLeakyReLuTest(backends);
+}
+
}
TEST_SUITE("Activation_GpuAccTests")
@@ -291,6 +329,12 @@
ActivationHardSwishTest(backends);
}
+TEST_CASE ("Activation_LeakyRelu_GpuAcc_Test")
+{
+ std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
+ ActivationLeakyReLuTest(backends);
+}
+
}
} // namespace armnnDelegate
\ No newline at end of file
diff --git a/delegate/test/ActivationTestHelper.hpp b/delegate/test/ActivationTestHelper.hpp
index e1901b7..b0a4d67 100644
--- a/delegate/test/ActivationTestHelper.hpp
+++ b/delegate/test/ActivationTestHelper.hpp
@@ -23,7 +23,8 @@
std::vector<char> CreateActivationTfLiteModel(tflite::BuiltinOperator activationOperatorCode,
tflite::TensorType tensorType,
- const std::vector <int32_t>& tensorShape)
+ const std::vector <int32_t>& tensorShape,
+ float alpha = 0)
{
using namespace tflite;
flatbuffers::FlatBufferBuilder flatBufferBuilder;
@@ -42,11 +43,24 @@
// create operator
const std::vector<int> operatorInputs{0};
const std::vector<int> operatorOutputs{1};
+
+ // builtin options
+ tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_NONE;
+ flatbuffers::Offset<void> operatorBuiltinOption = 0;
+
+ if (activationOperatorCode == tflite::BuiltinOperator_LEAKY_RELU)
+ {
+ operatorBuiltinOptionsType = tflite::BuiltinOptions_LeakyReluOptions;
+ operatorBuiltinOption = CreateLeakyReluOptions(flatBufferBuilder, alpha).Union();
+ }
+
flatbuffers::Offset <Operator> unaryOperator =
CreateOperator(flatBufferBuilder,
0,
flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
- flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()));
+ flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
+ operatorBuiltinOptionsType,
+ operatorBuiltinOption);
const std::vector<int> subgraphInputs{0};
const std::vector<int> subgraphOutputs{1};
@@ -78,13 +92,15 @@
void ActivationTest(tflite::BuiltinOperator activationOperatorCode,
std::vector<armnn::BackendId>& backends,
std::vector<float>& inputValues,
- std::vector<float>& expectedOutputValues)
+ std::vector<float>& expectedOutputValues,
+ float alpha = 0)
{
using namespace delegateTestInterpreter;
std::vector<int32_t> inputShape { { 4, 1, 4} };
std::vector<char> modelBuffer = CreateActivationTfLiteModel(activationOperatorCode,
::tflite::TensorType_FLOAT32,
- inputShape);
+ inputShape,
+ alpha);
// Setup interpreter with just TFLite Runtime.
auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);