IVGCVSW-3808 Add ElementwiseBinaryLayer
!android-nn-driver:9329
* Added ElementwiseBinaryLayer that can represent all ElementwiseBinary
operations including Add, Div, Sub, Maximum, Mul and Minimum.
* Updated Delegate to use ElementwiseBinaryLayer instead of the Add,
Div, Sub, Maximum, Mul and Minimum layers.
* Updated Deserializer to use ElementwiseBinaryLayer instead of the Add,
Div, Sub, Maximum, Mul and Minimum layers.
* Updated OnnxParser to use ElementwiseBinaryLayer instead of the Add
layer.
* Updated TfLiteParser to use ElementwiseBinaryLayer instead of the Add,
Div, Sub, Maximum, Mul and Minimum layers.
* Updated CL and Neon tests to use ElementwiseBinaryLayer.
* Updated CL and Neon Backend Specific Optimizations to accept
ElementBinaryLayers as well as Add, Div, Mul, Sub, Maximum and Minimum
layers.
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Change-Id: I7cbb96b60eb01f0e2b57b0541016d48a08b86c75
diff --git a/src/backends/backendsCommon/test/CMakeLists.txt b/src/backends/backendsCommon/test/CMakeLists.txt
index 509157a..77335d5 100644
--- a/src/backends/backendsCommon/test/CMakeLists.txt
+++ b/src/backends/backendsCommon/test/CMakeLists.txt
@@ -24,6 +24,7 @@
DetectionPostProcessEndToEndTestImpl.hpp
DynamicBackendTests.cpp
DynamicBackendTests.hpp
+ ElementwiseBinaryEndToEndTestImpl.hpp
ElementwiseUnaryEndToEndTestImpl.hpp
EndToEndTestImpl.hpp
FillEndToEndTestImpl.hpp
diff --git a/src/backends/backendsCommon/test/ElementwiseBinaryEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ElementwiseBinaryEndToEndTestImpl.hpp
new file mode 100644
index 0000000..6546a6a
--- /dev/null
+++ b/src/backends/backendsCommon/test/ElementwiseBinaryEndToEndTestImpl.hpp
@@ -0,0 +1,107 @@
+//
+// Copyright © 2023 Arm Ltd and contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "CommonTestUtils.hpp"
+
+#include <ResolveType.hpp>
+
+#include <armnn/INetwork.hpp>
+#include <armnn/utility/NumericCast.hpp>
+
+#include <doctest/doctest.h>
+
+#include <vector>
+
+namespace
+{
+
+template<armnn::DataType ArmnnTypeInput>
+INetworkPtr CreateElementwiseBinaryNetwork(const TensorShape& input1Shape,
+ const TensorShape& input2Shape,
+ const TensorShape& outputShape,
+ BinaryOperation operation,
+ const float qScale = 1.0f,
+ const int32_t qOffset = 0)
+{
+ using namespace armnn;
+
+ INetworkPtr net(INetwork::Create());
+
+ TensorInfo input1TensorInfo(input1Shape, ArmnnTypeInput, qScale, qOffset, true);
+ TensorInfo input2TensorInfo(input2Shape, ArmnnTypeInput, qScale, qOffset, true);
+ TensorInfo outputTensorInfo(outputShape, ArmnnTypeInput, qScale, qOffset);
+
+ IConnectableLayer* input1 = net->AddInputLayer(armnn::numeric_cast<LayerBindingId>(0));
+ IConnectableLayer* input2 = net->AddInputLayer(armnn::numeric_cast<LayerBindingId>(1));
+ IConnectableLayer* elementwiseBinaryLayer = net->AddElementwiseBinaryLayer(operation, "elementwiseUnary");
+ IConnectableLayer* output = net->AddOutputLayer(0, "output");
+
+ Connect(input1, elementwiseBinaryLayer, input1TensorInfo, 0, 0);
+ Connect(input2, elementwiseBinaryLayer, input2TensorInfo, 0, 1);
+ Connect(elementwiseBinaryLayer, output, outputTensorInfo, 0, 0);
+
+ return net;
+}
+
+template<armnn::DataType ArmnnInType,
+ typename TInput = armnn::ResolveType<ArmnnInType>>
+void ElementwiseBinarySimpleEndToEnd(const std::vector<BackendId>& backends,
+ BinaryOperation operation)
+{
+ using namespace armnn;
+
+ const float qScale = IsQuantizedType<TInput>() ? 0.25f : 1.0f;
+ const int32_t qOffset = IsQuantizedType<TInput>() ? 50 : 0;
+
+ const TensorShape& input1Shape = { 2, 2, 2, 2 };
+ const TensorShape& input2Shape = { 1 };
+ const TensorShape& outputShape = { 2, 2, 2, 2 };
+
+ // Builds up the structure of the network
+ INetworkPtr net = CreateElementwiseBinaryNetwork<ArmnnInType>(input1Shape, input2Shape, outputShape,
+ operation, qScale, qOffset);
+
+ CHECK(net);
+
+ const std::vector<float> input1({ 1, -1, 1, 1, 5, -5, 5, 5, -3, 3, 3, 3, 4, 4, -4, 4 });
+
+ const std::vector<float> input2({ 2 });
+ std::vector<float> expectedOutput;
+ switch (operation) {
+ case armnn::BinaryOperation::Add:
+ expectedOutput = { 3, 1, 3, 3, 7, -3, 7, 7, -1, 5, 5, 5, 6, 6, -2, 6 };
+ break;
+ case armnn::BinaryOperation::Div:
+ expectedOutput = {0.5f, -0.5f, 0.5f, 0.5f, 2.5f, -2.5f, 2.5f, 2.5f, -1.5f, 1.5f, 1.5f, 1.5f, 2, 2, -2, 2};
+ break;
+ case armnn::BinaryOperation::Maximum:
+ expectedOutput = { 2, 2, 2, 2, 5, 2, 5, 5, 2, 3, 3, 3, 4, 4, 2, 4 };
+ break;
+ case armnn::BinaryOperation::Minimum:
+ expectedOutput = { 1, -1, 1, 1, 2, -5, 2, 2, -3, 2, 2, 2, 2, 2, -4, 2 };
+ break;
+ case armnn::BinaryOperation::Mul:
+ expectedOutput = { 2, -2, 2, 2, 10, -10, 10, 10, -6, 6, 6, 6, 8, 8, -8, 8 };
+ break;
+ case armnn::BinaryOperation::Sub:
+ expectedOutput = { -1, -3, -1, -1, 3, -7, 3, 3, -5, 1, 1, 1, 2, 2, -6, 2 };
+ break;
+ default:
+ throw("Invalid Elementwise Binary operation");
+ }
+ const std::vector<float> expectedOutput_const = expectedOutput;
+ // quantize data
+ std::vector<TInput> qInput1Data = armnnUtils::QuantizedVector<TInput>(input1, qScale, qOffset);
+ std::vector<TInput> qInput2Data = armnnUtils::QuantizedVector<TInput>(input2, qScale, qOffset);
+ std::vector<TInput> qExpectedOutput = armnnUtils::QuantizedVector<TInput>(expectedOutput_const, qScale, qOffset);
+
+ std::map<int, std::vector<TInput>> inputTensorData = {{ 0, qInput1Data }, { 1, qInput2Data }};
+ std::map<int, std::vector<TInput>> expectedOutputData = {{ 0, qExpectedOutput }};
+
+ EndToEndLayerTestImpl<ArmnnInType, ArmnnInType>(std::move(net), inputTensorData, expectedOutputData, backends);
+}
+
+} // anonymous namespace
diff --git a/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp b/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp
index fb7a027..5b95d3c 100644
--- a/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp
+++ b/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2017,2022 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
@@ -664,6 +664,8 @@
DECLARE_LAYER_POLICY_2_PARAM(DetectionPostProcess)
+DECLARE_LAYER_POLICY_2_PARAM(ElementwiseBinary)
+
DECLARE_LAYER_POLICY_2_PARAM(ElementwiseUnary)
DECLARE_LAYER_POLICY_2_PARAM(FakeQuantization)
diff --git a/src/backends/backendsCommon/test/OptimizedNetworkTests.cpp b/src/backends/backendsCommon/test/OptimizedNetworkTests.cpp
index cd865de..5e619df 100644
--- a/src/backends/backendsCommon/test/OptimizedNetworkTests.cpp
+++ b/src/backends/backendsCommon/test/OptimizedNetworkTests.cpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
@@ -21,7 +21,7 @@
//Defines layers.
auto input = net->AddInputLayer(0);
- auto add = net->AddAdditionLayer();
+ auto add = net->AddElementwiseBinaryLayer(armnn::BinaryOperation::Add);
auto output = net->AddOutputLayer(0);
// Connects layers.
@@ -54,7 +54,7 @@
" edge [fontsize=8 fontcolor=\"blue\" fontname=\"arial-bold\"];\n"
" " << inputId << " [label=\"{Input|Guid : " << inputId << "\\lLayerType : Input\\l"
"BackendID : CpuRef\\l}\"];\n"
- " " << addId << " [label=\"{Addition|Guid : " << addId << "\\lLayerType : Addition\\l"
+ " " << addId << " [label=\"{ElementwiseBinary|Guid : " << addId << "\\lLayerType : ElementwiseBinary\\l"
"BackendID : CpuRef\\l}\"];\n"
" " << outputId << " [label=\"{Output|Guid : " << outputId << "\\lLayerType : Output\\l"
"BackendID : CpuRef\\l}\"];\n"
@@ -187,7 +187,7 @@
layer->GetOutputSlot(0).SetTensorInfo(desc);
armnn::IConnectableLayer* prevLayer = layer;
- layer = net->AddMultiplicationLayer("ml");
+ layer = net->AddElementwiseBinaryLayer(armnn::BinaryOperation::Mul, "ml");
prevLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
normLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1));
@@ -258,7 +258,7 @@
layer->GetOutputSlot(0).SetTensorInfo(desc);
armnn::IConnectableLayer* prevLayer = layer;
- layer = net->AddMultiplicationLayer("ml");
+ layer = net->AddElementwiseBinaryLayer(armnn::BinaryOperation::Mul, "ml");
prevLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
normLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1));
diff --git a/src/backends/backendsCommon/test/mockBackend/MockImportLayerSupport.hpp b/src/backends/backendsCommon/test/mockBackend/MockImportLayerSupport.hpp
index 380ce4a..da4b7ab 100644
--- a/src/backends/backendsCommon/test/mockBackend/MockImportLayerSupport.hpp
+++ b/src/backends/backendsCommon/test/mockBackend/MockImportLayerSupport.hpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2020-2021,2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
@@ -16,7 +16,7 @@
public:
bool IsLayerSupported(const LayerType& type,
const std::vector<TensorInfo>& infos,
- const BaseDescriptor& /*descriptor*/,
+ const BaseDescriptor& descriptor,
const Optional<LstmInputParamsInfo>& /*lstmParamsInfo*/,
const Optional<QuantizedLstmInputParamsInfo>& /*quantizedLstmParamsInfo*/,
Optional<std::string&> reasonIfUnsupported) const override
@@ -25,6 +25,11 @@
{
case LayerType::Addition:
return IsAdditionSupported(infos[0], infos[1], infos[2], reasonIfUnsupported);
+ case LayerType::ElementwiseBinary:
+ {
+ auto elementwiseDesc = *(PolymorphicDowncast<const ElementwiseBinaryDescriptor*>(&descriptor));
+ return (elementwiseDesc.m_Operation == BinaryOperation::Add);
+ }
case LayerType::Input:
return IsInputSupported(infos[0], reasonIfUnsupported);
case LayerType::Output: