From 762778817f6567f405d5d705f9c2131bab799e66 Mon Sep 17 00:00:00 2001 From: Conor Kennedy Date: Tue, 26 Feb 2019 08:29:54 +0000 Subject: IVGCVSW-2683 Add Serializer & Deserializer for Constant Change-Id: Iad7d89dfa963d9015cbe044f67aecc8bf6634b10 Signed-off-by: Conor Kennedy --- CMakeLists.txt | 1 + src/armnnDeserializer/Deserializer.cpp | 26 ++++ src/armnnDeserializer/Deserializer.hpp | 1 + src/armnnDeserializer/DeserializerSupport.md | 1 + src/armnnDeserializer/test/DeserializeConstant.cpp | 152 +++++++++++++++++++++ src/armnnSerializer/ArmnnSchema.fbs | 9 +- src/armnnSerializer/Serializer.cpp | 19 +++ src/armnnSerializer/Serializer.hpp | 4 + src/armnnSerializer/SerializerSupport.md | 1 + src/armnnSerializer/test/SerializerTests.cpp | 65 +++++++++ 10 files changed, 278 insertions(+), 1 deletion(-) create mode 100644 src/armnnDeserializer/test/DeserializeConstant.cpp diff --git a/CMakeLists.txt b/CMakeLists.txt index 7db728c52c..a40077680f 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -597,6 +597,7 @@ if(BUILD_UNIT_TESTS) src/armnnSerializer/test/SerializerTests.cpp src/armnnDeserializer/test/DeserializeActivation.cpp src/armnnDeserializer/test/DeserializeAdd.cpp + src/armnnDeserializer/test/DeserializeConstant.cpp src/armnnDeserializer/test/DeserializeConvolution2d.cpp src/armnnDeserializer/test/DeserializeFullyConnected.cpp src/armnnDeserializer/test/DeserializeMultiplication.cpp diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp index 09c0502886..b263c3a769 100644 --- a/src/armnnDeserializer/Deserializer.cpp +++ b/src/armnnDeserializer/Deserializer.cpp @@ -187,6 +187,7 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer) // register supported layers m_ParserFunctions[Layer_ActivationLayer] = &Deserializer::ParseActivation; m_ParserFunctions[Layer_AdditionLayer] = &Deserializer::ParseAdd; + m_ParserFunctions[Layer_ConstantLayer] = &Deserializer::ParseConstant; m_ParserFunctions[Layer_Convolution2dLayer] = &Deserializer::ParseConvolution2d; m_ParserFunctions[Layer_DepthwiseConvolution2dLayer] = &Deserializer::ParseDepthwiseConvolution2d; m_ParserFunctions[Layer_FullyConnectedLayer] = &Deserializer::ParseFullyConnected; @@ -207,6 +208,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt return graphPtr->layers()->Get(layerIndex)->layer_as_ActivationLayer()->base(); case Layer::Layer_AdditionLayer: return graphPtr->layers()->Get(layerIndex)->layer_as_AdditionLayer()->base(); + case Layer::Layer_ConstantLayer: + return graphPtr->layers()->Get(layerIndex)->layer_as_ConstantLayer()->base(); case Layer::Layer_Convolution2dLayer: return graphPtr->layers()->Get(layerIndex)->layer_as_Convolution2dLayer()->base(); case Layer::Layer_DepthwiseConvolution2dLayer: @@ -772,6 +775,29 @@ void Deserializer::ParseAdd(GraphPtr graph, unsigned int layerIndex) RegisterOutputSlots(graph, layerIndex, layer); } +void Deserializer::ParseConstant(GraphPtr graph, unsigned int layerIndex) +{ + CHECK_LAYERS(graph, 0, layerIndex); + CHECK_LOCATION(); + + auto outputs = GetOutputs(graph, layerIndex); + CHECK_VALID_SIZE(outputs.size(), 1); + + auto layerName = GetLayerName(graph, layerIndex); + + auto serializerLayer = graph->layers()->Get(layerIndex)->layer_as_ConstantLayer(); + auto serializerInput = serializerLayer->input(); + + armnn::ConstTensor input = ToConstTensor(serializerInput); + + IConnectableLayer* layer = m_Network->AddConstantLayer(input, layerName.c_str()); + + armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); + layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + RegisterOutputSlots(graph, layerIndex, layer); +} + void Deserializer::ParseConvolution2d(GraphPtr graph, unsigned int layerIndex) { CHECK_LAYERS(graph, 0, layerIndex); diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp index 94318e4062..9159ff2f36 100644 --- a/src/armnnDeserializer/Deserializer.hpp +++ b/src/armnnDeserializer/Deserializer.hpp @@ -70,6 +70,7 @@ private: void ParseUnsupportedLayer(GraphPtr graph, unsigned int layerIndex); void ParseActivation(GraphPtr graph, unsigned int layerIndex); void ParseAdd(GraphPtr graph, unsigned int layerIndex); + void ParseConstant(GraphPtr graph, unsigned int layerIndex); void ParseConvolution2d(GraphPtr graph, unsigned int layerIndex); void ParseDepthwiseConvolution2d(GraphPtr graph, unsigned int layerIndex); void ParseFullyConnected(GraphPtr graph, unsigned int layerIndex); diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md index 7e7ee06afe..988144425c 100644 --- a/src/armnnDeserializer/DeserializerSupport.md +++ b/src/armnnDeserializer/DeserializerSupport.md @@ -8,6 +8,7 @@ The Arm NN SDK Deserialize parser currently supports the following layers: * Activation * Addition +* Constant * Convolution2d * DepthwiseConvolution2d * FullyConnected diff --git a/src/armnnDeserializer/test/DeserializeConstant.cpp b/src/armnnDeserializer/test/DeserializeConstant.cpp new file mode 100644 index 0000000000..0abe5e6ca1 --- /dev/null +++ b/src/armnnDeserializer/test/DeserializeConstant.cpp @@ -0,0 +1,152 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include +#include "ParserFlatbuffersSerializeFixture.hpp" +#include "../Deserializer.hpp" + +#include +#include + +BOOST_AUTO_TEST_SUITE(DeserializeParser) + +struct ConstantAddFixture : public ParserFlatbuffersSerializeFixture +{ + explicit ConstantAddFixture(const std::string & shape, + const std::string & constTensorDatatype, + const std::string & constData, + const std::string & dataType) + { + m_JsonString = R"( + { + inputIds: [0], + 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: )" + shape + R"(, + dataType: )" + dataType + R"( + }, + }], + },}}, + }, + { + layer_type: "ConstantLayer", + layer: { + base: { + index:1, + layerName: "ConstantLayer", + layerType: "Constant", + outputSlots: [ { + index: 0, + tensorInfo: { + dimensions: )" + shape + R"(, + dataType: )" + dataType + R"(, + }, + }], + inputSlots: [{ + index: 0, + connection: {sourceLayerIndex:0, outputSlotIndex:0 }, + }], + }, + input: { + info: { + dimensions: )" + shape + R"(, + dataType: )" + dataType + R"( + }, + data_type: )" + constTensorDatatype + R"(, + data: { + data: )" + constData + R"(, + } } + }, + }, + { + layer_type: "AdditionLayer", + layer : { + base: { + index:2, + layerName: "AdditionLayer", + layerType: "Addition", + inputSlots: [ + { + index: 0, + connection: {sourceLayerIndex:0, outputSlotIndex:0 }, + }, + { + index: 1, + connection: {sourceLayerIndex:1, outputSlotIndex:0 }, + } + ], + outputSlots: [ { + index: 0, + tensorInfo: { + dimensions: )" + shape + R"(, + dataType: )" + dataType + R"( + }, + }], + }}, + }, + { + 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: )" + shape + R"(, + dataType: )" + dataType + R"( + }, + }], + }}}, + }] + } + )"; + SetupSingleInputSingleOutput("InputLayer1", "OutputLayer"); + } +}; + +struct SimpleConstantAddFixture : ConstantAddFixture +{ + SimpleConstantAddFixture() + : ConstantAddFixture("[ 2, 3 ]", // shape + "ByteData", // constDataType + "[ 1, 2, 3, 4, 5, 6 ]", // constData + "QuantisedAsymm8") // datatype + + {} +}; + +BOOST_FIXTURE_TEST_CASE(SimpleConstantAddQuantisedAsymm8, SimpleConstantAddFixture) +{ + RunTest<2, armnn::DataType::QuantisedAsymm8>( + 0, + { 1, 2, 3, 4, 5, 6 }, + { 2, 4, 6, 8, 10, 12 }); +} + +BOOST_AUTO_TEST_SUITE_END() \ No newline at end of file diff --git a/src/armnnSerializer/ArmnnSchema.fbs b/src/armnnSerializer/ArmnnSchema.fbs index dc14069798..db70e7bd4c 100644 --- a/src/armnnSerializer/ArmnnSchema.fbs +++ b/src/armnnSerializer/ArmnnSchema.fbs @@ -92,7 +92,8 @@ enum LayerType : uint { DepthwiseConvolution2d = 8, Activation = 9, Permute = 10, - FullyConnected = 11 + FullyConnected = 11, + Constant = 12 } // Base layer table to be used as part of other layers @@ -125,6 +126,11 @@ table AdditionLayer { base:LayerBase; } +table ConstantLayer { + base:LayerBase; + input:ConstTensor; +} + table Convolution2dLayer { base:LayerBase; descriptor:Convolution2dDescriptor; @@ -251,6 +257,7 @@ table PermuteDescriptor { union Layer { ActivationLayer, AdditionLayer, + ConstantLayer, Convolution2dLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, diff --git a/src/armnnSerializer/Serializer.cpp b/src/armnnSerializer/Serializer.cpp index a0a640e3b7..b8f5c3b555 100644 --- a/src/armnnSerializer/Serializer.cpp +++ b/src/armnnSerializer/Serializer.cpp @@ -141,6 +141,25 @@ void SerializerVisitor::VisitAdditionLayer(const armnn::IConnectableLayer* layer CreateAnyLayer(flatBufferAdditionLayer.o, serializer::Layer::Layer_AdditionLayer); } +// Build FlatBuffer for Constant Layer +void SerializerVisitor::VisitConstantLayer(const armnn::IConnectableLayer* layer, + const armnn::ConstTensor& input, + const char* name) +{ + // Create FlatBuffer BaseLayer + auto flatBufferConstantBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Constant); + + auto flatBufferConstTensorInfo = CreateConstTensorInfo(input); + + // Create the FlatBuffer ConstantLayer + auto flatBufferLayer = CreateConstantLayer(m_flatBufferBuilder, + flatBufferConstantBaseLayer, + flatBufferConstTensorInfo); + + // Add the AnyLayer to the FlatBufferLayers + CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_ConstantLayer); +} + // Build FlatBuffer for Convolution2dLayer void SerializerVisitor::VisitConvolution2dLayer(const armnn::IConnectableLayer* layer, const armnn::Convolution2dDescriptor& descriptor, diff --git a/src/armnnSerializer/Serializer.hpp b/src/armnnSerializer/Serializer.hpp index a423aa8a12..781648fa62 100644 --- a/src/armnnSerializer/Serializer.hpp +++ b/src/armnnSerializer/Serializer.hpp @@ -49,6 +49,10 @@ public: void VisitAdditionLayer(const armnn::IConnectableLayer* layer, const char* name = nullptr) override; + void VisitConstantLayer(const armnn::IConnectableLayer* layer, + const armnn::ConstTensor& input, + const char* = nullptr) override; + void VisitConvolution2dLayer(const armnn::IConnectableLayer* layer, const armnn::Convolution2dDescriptor& descriptor, const armnn::ConstTensor& weights, diff --git a/src/armnnSerializer/SerializerSupport.md b/src/armnnSerializer/SerializerSupport.md index 18e9f53a3d..9e84b63adc 100644 --- a/src/armnnSerializer/SerializerSupport.md +++ b/src/armnnSerializer/SerializerSupport.md @@ -8,6 +8,7 @@ The Arm NN SDK Serializer currently supports the following layers: * Activation * Addition +* Constant * Convolution2d * DepthwiseConvolution2d * FullyConnected diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp index bb050520a4..4e90dbe9e1 100644 --- a/src/armnnSerializer/test/SerializerTests.cpp +++ b/src/armnnSerializer/test/SerializerTests.cpp @@ -174,6 +174,71 @@ BOOST_AUTO_TEST_CASE(SerializeAddition) deserializedNetwork->Accept(nameChecker); } +BOOST_AUTO_TEST_CASE(SerializeConstant) +{ + armnn::INetworkPtr network = armnn::INetwork::Create(); + + armnn::ConstTensor inputTensor; + + armnn::IConnectableLayer* const inputLayer0 = network->AddConstantLayer(inputTensor, "constant"); + armnn::IConnectableLayer* const outputLayer0 = network->AddOutputLayer(0); + + inputLayer0->GetOutputSlot(0).Connect(outputLayer0->GetInputSlot(0)); + + armnnSerializer::Serializer serializer; + serializer.Serialize(*network); + + std::stringstream stream; + serializer.SaveSerializedToStream(stream); + BOOST_TEST(stream.str().length() > 0); + BOOST_TEST(stream.str().find("constant") != stream.str().npos); +} + +BOOST_AUTO_TEST_CASE(SerializeDeserializeConstant) +{ + class VerifyConstantName : public armnn::LayerVisitorBase + { + public: + void VisitConstantLayer(const armnn::IConnectableLayer*, const armnn::ConstTensor&, const char* name) override + { + BOOST_TEST(name == "constant"); + } + }; + + armnn::TensorInfo commonTensorInfo({ 2, 3 }, armnn::DataType::Float32); + + std::vector constantData = GenerateRandomData(commonTensorInfo.GetNumElements()); + armnn::ConstTensor constTensor(commonTensorInfo, constantData); + + // Builds up the structure of the network. + armnn::INetworkPtr net(armnn::INetwork::Create()); + + armnn::IConnectableLayer* input = net->AddInputLayer(0); + armnn::IConnectableLayer* constant = net->AddConstantLayer(constTensor, "constant"); + armnn::IConnectableLayer* add = net->AddAdditionLayer(); + armnn::IConnectableLayer* output = net->AddOutputLayer(0); + + input->GetOutputSlot(0).Connect(add->GetInputSlot(0)); + constant->GetOutputSlot(0).Connect(add->GetInputSlot(1)); + add->GetOutputSlot(0).Connect(output->GetInputSlot(0)); + + // Sets the tensors in the network. + input->GetOutputSlot(0).SetTensorInfo(commonTensorInfo); + constant->GetOutputSlot(0).SetTensorInfo(commonTensorInfo); + add->GetOutputSlot(0).SetTensorInfo(commonTensorInfo); + + armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*net)); + BOOST_CHECK(deserializedNetwork); + + VerifyConstantName nameChecker; + deserializedNetwork->Accept(nameChecker); + + CheckDeserializedNetworkAgainstOriginal(*net, + *deserializedNetwork, + commonTensorInfo.GetShape(), + commonTensorInfo.GetShape()); +} + BOOST_AUTO_TEST_CASE(SerializeMultiplication) { class VerifyMultiplicationName : public armnn::LayerVisitorBase -- cgit v1.2.1