From b9e6b5c3b96792f40201315c831db0aa257f286c Mon Sep 17 00:00:00 2001 From: Samuel Yap Date: Fri, 19 Aug 2022 11:14:38 +0100 Subject: IVGCVSW-7104: BatchMatMul Serializer/Deserializer Support * Updated FlatBuffers schema for BatchMatMul layer type * Added Serializer and Deserializer implementations for BatchMatMul * Added unit tests for BatchMatMul serialization and deserialization * Updated CMakeLists and docs Signed-off-by: Samuel Yap Change-Id: Iad63afbd036a3eb648683eb7416a475561aa20cb --- CMakeLists.txt | 1 + docs/05_02_deserializer_serializer.dox | 2 + src/armnnDeserializer/Deserializer.cpp | 34 ++++ src/armnnDeserializer/Deserializer.hpp | 1 + .../test/DeserializeBatchMatMul.cpp | 213 +++++++++++++++++++++ src/armnnSerializer/ArmnnSchema.fbs | 16 ++ src/armnnSerializer/Serializer.cpp | 36 ++++ src/armnnSerializer/Serializer.hpp | 4 + src/armnnSerializer/test/SerializerTests.cpp | 41 ++++ 9 files changed, 348 insertions(+) create mode 100644 src/armnnDeserializer/test/DeserializeBatchMatMul.cpp diff --git a/CMakeLists.txt b/CMakeLists.txt index c63d8fc0df..4e4818d232 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -775,6 +775,7 @@ if(BUILD_UNIT_TESTS) src/armnnDeserializer/test/DeserializeActivation.cpp src/armnnDeserializer/test/DeserializeAdd.cpp src/armnnDeserializer/test/DeserializeArgMinMax.cpp + src/armnnDeserializer/test/DeserializeBatchMatMul.cpp src/armnnDeserializer/test/DeserializeBatchToSpaceNd.cpp src/armnnDeserializer/test/DeserializeBatchNormalization.cpp src/armnnDeserializer/test/DeserializeCast.cpp diff --git a/docs/05_02_deserializer_serializer.dox b/docs/05_02_deserializer_serializer.dox index 6cfaf29968..c36e010323 100644 --- a/docs/05_02_deserializer_serializer.dox +++ b/docs/05_02_deserializer_serializer.dox @@ -22,6 +22,7 @@ The Arm NN SDK Serializer currently supports the following layers: - Activation - Addition - ArgMinMax +- BatchMatMul - BatchToSpaceNd - BatchNormalization - Cast @@ -114,6 +115,7 @@ The Arm NN SDK Deserialize parser currently supports the following layers: - Activation - Addition - ArgMinMax +- BatchMatMul - BatchToSpaceNd - BatchNormalization - Cast diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp index a405cb92a5..702b060512 100644 --- a/src/armnnDeserializer/Deserializer.cpp +++ b/src/armnnDeserializer/Deserializer.cpp @@ -214,6 +214,7 @@ m_ParserFunctions(Layer_MAX+1, &IDeserializer::DeserializerImpl::ParseUnsupporte m_ParserFunctions[Layer_ActivationLayer] = &DeserializerImpl::ParseActivation; m_ParserFunctions[Layer_AdditionLayer] = &DeserializerImpl::ParseAdd; m_ParserFunctions[Layer_ArgMinMaxLayer] = &DeserializerImpl::ParseArgMinMax; + m_ParserFunctions[Layer_BatchMatMulLayer] = &DeserializerImpl::ParseBatchMatMul; m_ParserFunctions[Layer_BatchToSpaceNdLayer] = &DeserializerImpl::ParseBatchToSpaceNd; m_ParserFunctions[Layer_BatchNormalizationLayer] = &DeserializerImpl::ParseBatchNormalization; m_ParserFunctions[Layer_CastLayer] = &DeserializerImpl::ParseCast; @@ -292,6 +293,8 @@ LayerBaseRawPtr IDeserializer::DeserializerImpl::GetBaseLayer(const GraphPtr& gr return graphPtr->layers()->Get(layerIndex)->layer_as_AdditionLayer()->base(); case Layer::Layer_ArgMinMaxLayer: return graphPtr->layers()->Get(layerIndex)->layer_as_ArgMinMaxLayer()->base(); + case Layer::Layer_BatchMatMulLayer: + return graphPtr->layers()->Get(layerIndex)->layer_as_BatchMatMulLayer()->base(); case Layer::Layer_BatchToSpaceNdLayer: return graphPtr->layers()->Get(layerIndex)->layer_as_BatchToSpaceNdLayer()->base(); case Layer::Layer_BatchNormalizationLayer: @@ -1258,6 +1261,37 @@ void IDeserializer::DeserializerImpl::ParseArgMinMax(GraphPtr graph, unsigned in RegisterOutputSlots(graph, layerIndex, layer); } +void IDeserializer::DeserializerImpl::ParseBatchMatMul(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 serializerLayer = graph->layers()->Get(layerIndex)->layer_as_BatchMatMulLayer(); + auto serializerDescriptor = serializerLayer->descriptor(); + + armnn::BatchMatMulDescriptor descriptor(serializerDescriptor->transposeX(), + serializerDescriptor->transposeY(), + serializerDescriptor->adjointX(), + serializerDescriptor->adjointY(), + ToDataLayout(serializerDescriptor->dataLayoutX()), + ToDataLayout(serializerDescriptor->dataLayoutY())); + + auto layerName = GetLayerName(graph, layerIndex); + IConnectableLayer* layer = m_Network->AddBatchMatMulLayer(descriptor, layerName.c_str()); + + armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); + layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + RegisterInputSlots(graph, layerIndex, layer); + RegisterOutputSlots(graph, layerIndex, layer); +} + void IDeserializer::DeserializerImpl::ParseBatchToSpaceNd(GraphPtr graph, unsigned int layerIndex) { CHECK_LAYERS(graph, 0, layerIndex); diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp index 277c09ae48..bd01a35431 100644 --- a/src/armnnDeserializer/Deserializer.hpp +++ b/src/armnnDeserializer/Deserializer.hpp @@ -88,6 +88,7 @@ private: void ParseActivation(GraphPtr graph, unsigned int layerIndex); void ParseAdd(GraphPtr graph, unsigned int layerIndex); void ParseArgMinMax(GraphPtr graph, unsigned int layerIndex); + void ParseBatchMatMul(GraphPtr graph, unsigned int layerIndex); void ParseBatchToSpaceNd(GraphPtr graph, unsigned int layerIndex); void ParseBatchNormalization(GraphPtr graph, unsigned int layerIndex); void ParseCast(GraphPtr graph, unsigned int layerIndex); diff --git a/src/armnnDeserializer/test/DeserializeBatchMatMul.cpp b/src/armnnDeserializer/test/DeserializeBatchMatMul.cpp new file mode 100644 index 0000000000..40f93ce420 --- /dev/null +++ b/src/armnnDeserializer/test/DeserializeBatchMatMul.cpp @@ -0,0 +1,213 @@ +// +// Copyright © 2022 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ParserFlatbuffersSerializeFixture.hpp" +#include + +#include + +#include + +TEST_SUITE("Deserializer_BatchMatMul") +{ +struct BatchMatMulFixture : public ParserFlatbuffersSerializeFixture +{ + explicit BatchMatMulFixture(const std::string& inputXShape, + const std::string& inputYShape, + const std::string& outputShape, + const std::string& dataType) + { + m_JsonString = R"( + { + inputIds:[ + 0, + 1 + ], + outputIds:[ + 3 + ], + layers:[ + { + layer_type:"InputLayer", + layer:{ + base:{ + layerBindingId:0, + base:{ + index:0, + layerName:"InputXLayer", + layerType:"Input", + inputSlots:[ + { + index:0, + connection:{ + sourceLayerIndex:0, + outputSlotIndex:0 + }, + + } + ], + outputSlots:[ + { + index:0, + tensorInfo:{ + dimensions:)" + inputXShape + R"(, + dataType:)" + dataType + R"( + }, + + } + ], + + }, + + } + }, + + }, + { + layer_type:"InputLayer", + layer:{ + base:{ + layerBindingId:1, + base:{ + index:1, + layerName:"InputYLayer", + layerType:"Input", + inputSlots:[ + { + index:0, + connection:{ + sourceLayerIndex:0, + outputSlotIndex:0 + }, + + } + ], + outputSlots:[ + { + index:0, + tensorInfo:{ + dimensions:)" + inputYShape + R"(, + dataType:)" + dataType + R"( + }, + + } + ], + + }, + + } + }, + + }, + { + layer_type:"BatchMatMulLayer", + layer:{ + base:{ + index:2, + layerName:"BatchMatMulLayer", + layerType:"BatchMatMul", + inputSlots:[ + { + index:0, + connection:{ + sourceLayerIndex:0, + outputSlotIndex:0 + }, + + }, + { + index:1, + connection:{ + sourceLayerIndex:1, + outputSlotIndex:0 + }, + + } + ], + outputSlots:[ + { + index:0, + tensorInfo:{ + dimensions:)" + outputShape + R"(, + dataType:)" + dataType + R"( + }, + + } + ], + + }, + descriptor:{ + transposeX:false, + transposeY:false, + adjointX:false, + adjointY:false, + dataLayoutX:NHWC, + dataLayoutY:NHWC + } + }, + + }, + { + 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:)" + dataType + R"( + }, + + } + ], + + } + } + }, + + } + ] + } + )"; + Setup(); + } +}; + +struct SimpleBatchMatMulFixture : BatchMatMulFixture +{ + SimpleBatchMatMulFixture() + : BatchMatMulFixture("[ 1, 2, 2, 1 ]", + "[ 1, 2, 2, 1 ]", + "[ 1, 2, 2, 1 ]", + "Float32") + {} +}; + +TEST_CASE_FIXTURE(SimpleBatchMatMulFixture, "SimpleBatchMatMulTest") +{ + RunTest<4, armnn::DataType::Float32>( + 0, + {{"InputXLayer", { 1.0f, 2.0f, 3.0f, 4.0f }}, + {"InputYLayer", { 5.0f, 6.0f, 7.0f, 8.0f }}}, + {{"OutputLayer", { 19.0f, 22.0f, 43.0f, 50.0f }}}); +} + +} \ No newline at end of file diff --git a/src/armnnSerializer/ArmnnSchema.fbs b/src/armnnSerializer/ArmnnSchema.fbs index f301fce818..2dbfd85b23 100644 --- a/src/armnnSerializer/ArmnnSchema.fbs +++ b/src/armnnSerializer/ArmnnSchema.fbs @@ -182,6 +182,7 @@ enum LayerType : uint { Convolution3d = 65, Pooling3d = 66, GatherNd = 67, + BatchMatMul = 68, } // Base layer table to be used as part of other layers @@ -1009,6 +1010,20 @@ table UnidirectionalSequenceLstmLayer { inputParams:LstmInputParams; } +table BatchMatMulDescriptor { + transposeX:bool = false; + transposeY:bool = false; + adjointX:bool = false; + adjointY:bool = false; + dataLayoutX:DataLayout = NCHW; + dataLayoutY:DataLayout = NCHW; +} + +table BatchMatMulLayer { + base:LayerBase; + descriptor:BatchMatMulDescriptor; +} + union Layer { ActivationLayer, AdditionLayer, @@ -1078,6 +1093,7 @@ union Layer { Convolution3dLayer, Pooling3dLayer, GatherNdLayer, + BatchMatMulLayer, } table AnyLayer { diff --git a/src/armnnSerializer/Serializer.cpp b/src/armnnSerializer/Serializer.cpp index 488dac6186..c9a3022b8d 100644 --- a/src/armnnSerializer/Serializer.cpp +++ b/src/armnnSerializer/Serializer.cpp @@ -218,6 +218,33 @@ void SerializerStrategy::SerializeArgMinMaxLayer(const armnn::IConnectableLayer CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_ArgMinMaxLayer); } +void SerializerStrategy::SerializeBatchMatMulLayer(const armnn::IConnectableLayer* layer, + const armnn::BatchMatMulDescriptor& descriptor, + const char* name) +{ + IgnoreUnused(name); + + // Create FlatBuffer BaseLayer + auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_BatchMatMul); + + // Create the FlatBuffer BatchMatMulDescriptor + auto flatBufferDescriptor = CreateBatchMatMulDescriptor(m_flatBufferBuilder, + descriptor.m_TransposeX, + descriptor.m_TransposeY, + descriptor.m_AdjointX, + descriptor.m_AdjointY, + GetFlatBufferDataLayout(descriptor.m_DataLayoutX), + GetFlatBufferDataLayout(descriptor.m_DataLayoutY)); + + // Create the FlatBuffer BatchMatMulLayer + auto flatBufferBatchMatMulLayer = CreateBatchMatMulLayer(m_flatBufferBuilder, + flatBufferBaseLayer, + flatBufferDescriptor); + + // Add the AnyLayer to the FlatBufferLayers + CreateAnyLayer(flatBufferBatchMatMulLayer.o, serializer::Layer::Layer_BatchMatMulLayer); +} + // Build FlatBuffer for BatchToSpaceNd Layer void SerializerStrategy::SerializeBatchToSpaceNdLayer(const armnn::IConnectableLayer* layer, const armnn::BatchToSpaceNdDescriptor& descriptor, @@ -1971,6 +1998,15 @@ void SerializerStrategy::ExecuteStrategy(const armnn::IConnectableLayer* layer, SerializeArgMinMaxLayer(layer, layerDescriptor, name); break; } + case armnn::LayerType::BatchMatMul: + { + const armnn::BatchMatMulDescriptor& layerDescriptor = + static_cast(descriptor); + SerializeBatchMatMulLayer(layer, + layerDescriptor, + name); + break; + } case armnn::LayerType::BatchNormalization : { const armnn::BatchNormalizationDescriptor& layerDescriptor = diff --git a/src/armnnSerializer/Serializer.hpp b/src/armnnSerializer/Serializer.hpp index 216f4dc016..60fed4f6df 100644 --- a/src/armnnSerializer/Serializer.hpp +++ b/src/armnnSerializer/Serializer.hpp @@ -113,6 +113,10 @@ private: const armnn::ArgMinMaxDescriptor& argMinMaxDescriptor, const char* name = nullptr); + void SerializeBatchMatMulLayer(const armnn::IConnectableLayer* layer, + const armnn::BatchMatMulDescriptor& descriptor, + const char* name = nullptr); + void SerializeBatchToSpaceNdLayer(const armnn::IConnectableLayer* layer, const armnn::BatchToSpaceNdDescriptor& descriptor, const char* name = nullptr); diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp index 3c00fc43ae..a568bf15c9 100644 --- a/src/armnnSerializer/test/SerializerTests.cpp +++ b/src/armnnSerializer/test/SerializerTests.cpp @@ -92,6 +92,47 @@ TEST_CASE("SerializeArgMinMaxSigned64") SerializeArgMinMaxTest(armnn::DataType::Signed64); } +TEST_CASE("SerializeBatchMatMul") +{ + const std::string layerName("batchMatMul"); + const armnn::TensorInfo inputXInfo({2, 3, 4, 5}, armnn::DataType::Float32); + const armnn::TensorInfo inputYInfo({2, 4, 3, 5}, armnn::DataType::Float32); + + const armnn::TensorInfo outputInfo({2, 3, 3, 5}, armnn::DataType::Float32); + + armnn::BatchMatMulDescriptor descriptor(false, + false, + false, + false, + armnn::DataLayout::NHWC, + armnn::DataLayout::NHWC); + + armnn::INetworkPtr network = armnn::INetwork::Create(); + armnn::IConnectableLayer* const inputXLayer = network->AddInputLayer(0); + armnn::IConnectableLayer* const inputYLayer = network->AddInputLayer(1); + + armnn::IConnectableLayer* const batchMatMulLayer = + network->AddBatchMatMulLayer(descriptor, layerName.c_str()); + armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); + + inputXLayer->GetOutputSlot(0).Connect(batchMatMulLayer->GetInputSlot(0)); + inputYLayer->GetOutputSlot(0).Connect(batchMatMulLayer->GetInputSlot(1)); + batchMatMulLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); + + inputXLayer->GetOutputSlot(0).SetTensorInfo(inputXInfo); + inputYLayer->GetOutputSlot(0).SetTensorInfo(inputYInfo); + batchMatMulLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); + + armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); + CHECK(deserializedNetwork); + + LayerVerifierBaseWithDescriptor verifier(layerName, + {inputXInfo, inputYInfo}, + {outputInfo}, + descriptor); + deserializedNetwork->ExecuteStrategy(verifier); +} + TEST_CASE("SerializeBatchNormalization") { const std::string layerName("batchNormalization"); -- cgit v1.2.1