From 79ffdf57b12da6ed3fe70e62311af6c4661a9bd3 Mon Sep 17 00:00:00 2001 From: Conor Kennedy Date: Fri, 1 Mar 2019 14:24:54 +0000 Subject: IVGCVSW-2692 Add Serializer and Deserializer for Greater Change-Id: I344a1f36a8a4ab601dd4d62a0014c554ceb6a1c6 Signed-off-by: Conor Kennedy --- CMakeLists.txt | 1 + src/armnnDeserializer/Deserializer.cpp | 23 +++ src/armnnDeserializer/Deserializer.hpp | 1 + src/armnnDeserializer/DeserializerSupport.md | 1 + src/armnnDeserializer/test/DeserializeGreater.cpp | 182 ++++++++++++++++++++++ src/armnnSerializer/ArmnnSchema.fbs | 11 +- src/armnnSerializer/Serializer.cpp | 8 + src/armnnSerializer/Serializer.hpp | 3 + src/armnnSerializer/SerializerSupport.md | 1 + src/armnnSerializer/test/SerializerTests.cpp | 41 +++++ 10 files changed, 269 insertions(+), 3 deletions(-) create mode 100644 src/armnnDeserializer/test/DeserializeGreater.cpp diff --git a/CMakeLists.txt b/CMakeLists.txt index 0c8a7b906a..f3ad333f96 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -605,6 +605,7 @@ if(BUILD_UNIT_TESTS) src/armnnDeserializer/test/DeserializeEqual.cpp src/armnnDeserializer/test/DeserializeFloor.cpp src/armnnDeserializer/test/DeserializeFullyConnected.cpp + src/armnnDeserializer/test/DeserializeGreater.cpp src/armnnDeserializer/test/DeserializeMultiplication.cpp src/armnnDeserializer/test/DeserializeNormalization.cpp src/armnnDeserializer/test/DeserializePad.cpp diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp index e8cda2e3d3..aebdf0e52c 100644 --- a/src/armnnDeserializer/Deserializer.cpp +++ b/src/armnnDeserializer/Deserializer.cpp @@ -196,6 +196,7 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer) m_ParserFunctions[Layer_EqualLayer] = &Deserializer::ParseEqual; m_ParserFunctions[Layer_FullyConnectedLayer] = &Deserializer::ParseFullyConnected; m_ParserFunctions[Layer_FloorLayer] = &Deserializer::ParseFloor; + m_ParserFunctions[Layer_GreaterLayer] = &Deserializer::ParseGreater; m_ParserFunctions[Layer_MinimumLayer] = &Deserializer::ParseMinimum; m_ParserFunctions[Layer_MaximumLayer] = &Deserializer::ParseMaximum; m_ParserFunctions[Layer_MultiplicationLayer] = &Deserializer::ParseMultiplication; @@ -237,6 +238,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt return graphPtr->layers()->Get(layerIndex)->layer_as_FullyConnectedLayer()->base(); case Layer::Layer_FloorLayer: return graphPtr->layers()->Get(layerIndex)->layer_as_FloorLayer()->base(); + case Layer::Layer_GreaterLayer: + return graphPtr->layers()->Get(layerIndex)->layer_as_GreaterLayer()->base(); case Layer::Layer_InputLayer: return graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->base(); case Layer::Layer_MinimumLayer: @@ -1036,6 +1039,26 @@ void Deserializer::ParseEqual(GraphPtr graph, unsigned int layerIndex) RegisterOutputSlots(graph, layerIndex, layer); } +void Deserializer::ParseGreater(GraphPtr graph, unsigned int layerIndex) +{ + CHECK_LAYERS(graph, 0, layerIndex); + auto inputs = GetInputs(graph, layerIndex); + CHECK_LOCATION(); + CHECK_VALID_SIZE(inputs.size(), 2); + + auto outputs = GetOutputs(graph, layerIndex); + CHECK_VALID_SIZE(outputs.size(), 1); + + auto layerName = GetLayerName(graph, layerIndex); + IConnectableLayer* layer = m_Network->AddGreaterLayer(layerName.c_str()); + + armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); + layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + RegisterInputSlots(graph, layerIndex, layer); + RegisterOutputSlots(graph, layerIndex, layer); +} + void Deserializer::ParseMinimum(GraphPtr graph, unsigned int layerIndex) { CHECK_LAYERS(graph, 0, layerIndex); diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp index 237cb9f975..7e25534763 100644 --- a/src/armnnDeserializer/Deserializer.hpp +++ b/src/armnnDeserializer/Deserializer.hpp @@ -82,6 +82,7 @@ private: void ParseEqual(GraphPtr graph, unsigned int layerIndex); void ParseFloor(GraphPtr graph, unsigned int layerIndex); void ParseFullyConnected(GraphPtr graph, unsigned int layerIndex); + void ParseGreater(GraphPtr graph, unsigned int layerIndex); void ParseMinimum(GraphPtr graph, unsigned int layerIndex); void ParseMaximum(GraphPtr graph, unsigned int layerIndex); void ParseMultiplication(GraphPtr graph, unsigned int layerIndex); diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md index b5e9b6b0a2..ba85a04bb2 100644 --- a/src/armnnDeserializer/DeserializerSupport.md +++ b/src/armnnDeserializer/DeserializerSupport.md @@ -17,6 +17,7 @@ The Arm NN SDK Deserialize parser currently supports the following layers: * Equal * Floor * FullyConnected +* Greater * Maximum * Minimum * Multiplication diff --git a/src/armnnDeserializer/test/DeserializeGreater.cpp b/src/armnnDeserializer/test/DeserializeGreater.cpp new file mode 100644 index 0000000000..d1ff250d3d --- /dev/null +++ b/src/armnnDeserializer/test/DeserializeGreater.cpp @@ -0,0 +1,182 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include +#include "ParserFlatbuffersSerializeFixture.hpp" +#include "../Deserializer.hpp" + +#include +#include + +BOOST_AUTO_TEST_SUITE(Deserializer) + +struct GreaterFixture : public ParserFlatbuffersSerializeFixture +{ + explicit GreaterFixture(const std::string & inputShape1, + const std::string & inputShape2, + const std::string & outputShape, + const std::string & inputDataType, + const std::string & outputDataType) + { + m_JsonString = R"( + { + inputIds: [0, 1], + outputIds: [3], + layers: [ + { + layer_type: "InputLayer", + layer: { + base: { + layerBindingId: 0, + base: { + index: 0, + layerName: "InputLayer1", + layerType: "Input", + inputSlots: [{ + index: 0, + connection: {sourceLayerIndex:0, outputSlotIndex:0 }, + }], + outputSlots: [ { + index: 0, + tensorInfo: { + dimensions: )" + inputShape1 + R"(, + dataType: )" + inputDataType + R"( + }, + }], + },}}, + }, + { + layer_type: "InputLayer", + layer: { + base: { + layerBindingId: 1, + base: { + index:1, + layerName: "InputLayer2", + layerType: "Input", + inputSlots: [{ + index: 0, + connection: {sourceLayerIndex:0, outputSlotIndex:0 }, + }], + outputSlots: [ { + index: 0, + tensorInfo: { + dimensions: )" + inputShape2 + R"(, + dataType: )" + inputDataType + R"( + }, + }], + },}}, + }, + { + layer_type: "GreaterLayer", + layer : { + base: { + index:2, + layerName: "GreaterLayer", + layerType: "Greater", + inputSlots: [ + { + index: 0, + connection: {sourceLayerIndex:0, outputSlotIndex:0 }, + }, + { + index: 1, + connection: {sourceLayerIndex:1, outputSlotIndex:0 }, + } + ], + outputSlots: [ { + index: 0, + tensorInfo: { + dimensions: )" + outputShape + R"(, + dataType: Boolean + }, + }], + }}, + }, + { + layer_type: "OutputLayer", + layer: { + base:{ + layerBindingId: 0, + base: { + index: 3, + layerName: "OutputLayer", + layerType: "Output", + inputSlots: [{ + index: 0, + connection: {sourceLayerIndex:2, outputSlotIndex:0 }, + }], + outputSlots: [ { + index: 0, + tensorInfo: { + dimensions: )" + outputShape + R"(, + dataType: )" + outputDataType + R"( + }, + }], + }}}, + }] + } + )"; + Setup(); + } +}; + + +struct SimpleGreaterFixtureQuantisedAsymm8 : GreaterFixture +{ + SimpleGreaterFixtureQuantisedAsymm8() : GreaterFixture("[ 2, 2 ]", // input1Shape + "[ 2, 2 ]", // input2Shape + "[ 2, 2 ]", // outputShape + "QuantisedAsymm8", // inputDataType + "Float32") {} // outputDataType +}; + +struct SimpleGreaterFixtureFloat32 : GreaterFixture +{ + SimpleGreaterFixtureFloat32() : GreaterFixture("[ 2, 2, 1, 1 ]", // input1Shape + "[ 2, 2, 1, 1 ]", // input2Shape + "[ 2, 2, 1, 1 ]", // outputShape + "Float32", // inputDataType + "Float32") {} // outputDataType +}; + +struct SimpleGreaterFixtureBroadcast : GreaterFixture +{ + SimpleGreaterFixtureBroadcast() : GreaterFixture("[ 1, 2, 2, 2 ]", // input1Shape + "[ 1, 1, 1, 1 ]", // input2Shape + "[ 1, 2, 2, 2 ]", // outputShape + "Float32", // inputDataType + "Float32") {} // outputDataType +}; + + +BOOST_FIXTURE_TEST_CASE(GreaterQuantisedAsymm8, SimpleGreaterFixtureQuantisedAsymm8) +{ + RunTest<2, armnn::DataType::QuantisedAsymm8, armnn::DataType::Boolean>( + 0, + {{"InputLayer1", { 1, 5, 8, 7 }}, + { "InputLayer2", { 4, 0, 6, 7 }}}, + {{"OutputLayer", { 0, 1, 1, 0 }}}); +} + +BOOST_FIXTURE_TEST_CASE(GreaterFloat32, SimpleGreaterFixtureFloat32) +{ + RunTest<4, armnn::DataType::Float32, armnn::DataType::Boolean>( + 0, + {{"InputLayer1", { 1.0f, 2.0f, 3.0f, 4.0f }}, + { "InputLayer2", { 1.0f, 5.0f, 2.0f, 2.0f }}}, + {{"OutputLayer", { 0, 0, 1, 1 }}}); +} + +BOOST_FIXTURE_TEST_CASE(GreaterBroadcast, SimpleGreaterFixtureBroadcast) +{ + RunTest<4, armnn::DataType::Float32, armnn::DataType::Boolean>( + 0, + {{"InputLayer1", { 1, 2, 3, 4, 5, 6, 7, 8 }}, + {"InputLayer2", { 1 }}}, + {{"OutputLayer", { 0, 1, 1, 1, 1, 1, 1, 1 }}}); +} + +BOOST_AUTO_TEST_SUITE_END() diff --git a/src/armnnSerializer/ArmnnSchema.fbs b/src/armnnSerializer/ArmnnSchema.fbs index f416912618..410849ec8b 100644 --- a/src/armnnSerializer/ArmnnSchema.fbs +++ b/src/armnnSerializer/ArmnnSchema.fbs @@ -104,7 +104,8 @@ enum LayerType : uint { Pad = 20, Rsqrt = 21, Floor = 22, - BatchNormalization = 23 + BatchNormalization = 23, + Greater = 24 } // Base layer table to be used as part of other layers @@ -184,6 +185,10 @@ table FullyConnectedDescriptor { transposeWeightsMatrix:bool = false; } +table GreaterLayer { + base:LayerBase; +} + table InputLayer { base:BindableLayerBase; } @@ -341,7 +346,6 @@ table PadDescriptor { padList:[uint]; } - table RsqrtLayer { base:LayerBase; } @@ -384,7 +388,8 @@ union Layer { NormalizationLayer, PadLayer, RsqrtLayer, - FloorLayer + FloorLayer, + GreaterLayer } table AnyLayer { diff --git a/src/armnnSerializer/Serializer.cpp b/src/armnnSerializer/Serializer.cpp index 423706ceb3..b55adb266d 100644 --- a/src/armnnSerializer/Serializer.cpp +++ b/src/armnnSerializer/Serializer.cpp @@ -329,6 +329,14 @@ void SerializerVisitor::VisitMaximumLayer(const armnn::IConnectableLayer* layer, CreateAnyLayer(fbMaximumLayer.o, serializer::Layer::Layer_MaximumLayer); } +void SerializerVisitor::VisitGreaterLayer(const armnn::IConnectableLayer* layer, const char* name) +{ + auto fbGreaterBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Greater); + auto fbGreaterLayer = serializer::CreateGreaterLayer(m_flatBufferBuilder, fbGreaterBaseLayer); + + CreateAnyLayer(fbGreaterLayer.o, serializer::Layer::Layer_GreaterLayer); +} + // Build FlatBuffer for Multiplication Layer void SerializerVisitor::VisitMultiplicationLayer(const armnn::IConnectableLayer* layer, const char* name) { diff --git a/src/armnnSerializer/Serializer.hpp b/src/armnnSerializer/Serializer.hpp index a60d19b860..164db19e6a 100644 --- a/src/armnnSerializer/Serializer.hpp +++ b/src/armnnSerializer/Serializer.hpp @@ -92,6 +92,9 @@ public: const armnn::Optional& biases, const char* name = nullptr) override; + void VisitGreaterLayer(const armnn::IConnectableLayer* layer, + const char* name = nullptr) override; + void VisitInputLayer(const armnn::IConnectableLayer* layer, armnn::LayerBindingId id, const char* name = nullptr) override; diff --git a/src/armnnSerializer/SerializerSupport.md b/src/armnnSerializer/SerializerSupport.md index 98023a6771..f18ef3af68 100644 --- a/src/armnnSerializer/SerializerSupport.md +++ b/src/armnnSerializer/SerializerSupport.md @@ -17,6 +17,7 @@ The Arm NN SDK Serializer currently supports the following layers: * Equal * Floor * FullyConnected +* Greater * Maximum * Minimum * Multiplication diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp index 3ef15831b1..7206d6dc53 100644 --- a/src/armnnSerializer/test/SerializerTests.cpp +++ b/src/armnnSerializer/test/SerializerTests.cpp @@ -508,6 +508,47 @@ BOOST_AUTO_TEST_CASE(SerializeDeserializeConvolution2d) {outputInfo.GetShape()}); } +BOOST_AUTO_TEST_CASE(SerializeDeserializeGreater) +{ + class VerifyGreaterName : public armnn::LayerVisitorBase + { + public: + void VisitGreaterLayer(const armnn::IConnectableLayer*, const char* name) override + { + BOOST_TEST(name == "greater"); + } + }; + + const armnn::TensorInfo inputTensorInfo1({ 1, 2, 2, 2 }, armnn::DataType::Float32); + const armnn::TensorInfo inputTensorInfo2({ 1, 2, 2, 2 }, armnn::DataType::Float32); + const armnn::TensorInfo outputTensorInfo({ 1, 2, 2, 2 }, armnn::DataType::Boolean); + + armnn::INetworkPtr network = armnn::INetwork::Create(); + armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(0); + armnn::IConnectableLayer* const inputLayer2 = network->AddInputLayer(1); + armnn::IConnectableLayer* const greaterLayer = network->AddGreaterLayer("greater"); + armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); + + inputLayer1->GetOutputSlot(0).Connect(greaterLayer->GetInputSlot(0)); + inputLayer1->GetOutputSlot(0).SetTensorInfo(inputTensorInfo1); + inputLayer2->GetOutputSlot(0).Connect(greaterLayer->GetInputSlot(1)); + inputLayer2->GetOutputSlot(0).SetTensorInfo(inputTensorInfo2); + greaterLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); + greaterLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); + BOOST_CHECK(deserializedNetwork); + + VerifyGreaterName nameChecker; + deserializedNetwork->Accept(nameChecker); + + CheckDeserializedNetworkAgainstOriginal(*network, + *deserializedNetwork, + {inputTensorInfo1.GetShape(), inputTensorInfo2.GetShape()}, + {outputTensorInfo.GetShape()}, + {0, 1}); +} + BOOST_AUTO_TEST_CASE(SerializeDeserializeReshape) { class VerifyReshapeName : public armnn::LayerVisitorBase -- cgit v1.2.1