IVGCVSW-2644 Add Serializer & Deserializer for Softmax
Change-Id: Ifea2108e173d2b602162fe53b880a68e1c715510
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
diff --git a/src/armnnDeserializeParser/DeserializeParser.cpp b/src/armnnDeserializeParser/DeserializeParser.cpp
index 6a6a0fa..eb7bcca 100644
--- a/src/armnnDeserializeParser/DeserializeParser.cpp
+++ b/src/armnnDeserializeParser/DeserializeParser.cpp
@@ -28,9 +28,11 @@
using namespace armnn;
using namespace armnn::armnnSerializer;
-namespace armnnDeserializeParser {
+namespace armnnDeserializeParser
+{
-namespace {
+namespace
+{
const uint32_t VIRTUAL_LAYER_ID = std::numeric_limits<uint32_t>::max();
@@ -132,8 +134,9 @@
m_ParserFunctions(Layer_MAX+1, &DeserializeParser::ParseUnsupportedLayer)
{
// register supported layers
- m_ParserFunctions[Layer_AdditionLayer] = &DeserializeParser::ParseAdd;
- m_ParserFunctions[Layer_MultiplicationLayer] = &DeserializeParser::ParseMultiplication;
+ m_ParserFunctions[Layer_AdditionLayer] = &DeserializeParser::ParseAdd;
+ m_ParserFunctions[Layer_MultiplicationLayer] = &DeserializeParser::ParseMultiplication;
+ m_ParserFunctions[Layer_SoftmaxLayer] = &DeserializeParser::ParseSoftmax;
}
DeserializeParser::LayerBaseRawPtr DeserializeParser::GetBaseLayer(const GraphPtr& graphPtr, unsigned int layerIndex)
@@ -150,6 +153,8 @@
return graphPtr->layers()->Get(layerIndex)->layer_as_MultiplicationLayer()->base();
case Layer::Layer_OutputLayer:
return graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->base();
+ case Layer::Layer_SoftmaxLayer:
+ return graphPtr->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->base();
case Layer::Layer_NONE:
default:
throw ParseException(boost::str(
@@ -606,4 +611,27 @@
RegisterOutputSlots(layerIndex, layer);
}
+void DeserializeParser::ParseSoftmax(unsigned int layerIndex)
+{
+ CHECK_LAYERS(m_Graph, 0, layerIndex);
+
+ DeserializeParser::TensorRawPtrVector inputs = GetInputs(m_Graph, layerIndex);
+ CHECK_VALID_SIZE(inputs.size(), 1);
+
+ DeserializeParser::TensorRawPtrVector outputs = GetOutputs(m_Graph, layerIndex);
+ CHECK_VALID_SIZE(outputs.size(), 1);
+
+ armnn::SoftmaxDescriptor descriptor;
+ descriptor.m_Beta = m_Graph->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->descriptor()->beta();
+
+ const std::string layerName = boost::str(boost::format("Softmax:%1%") % layerIndex);
+ IConnectableLayer* layer = m_Network->AddSoftmaxLayer(descriptor, layerName.c_str());
+
+ armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+ layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ RegisterInputSlots(layerIndex, layer);
+ RegisterOutputSlots(layerIndex, layer);
}
+
+} // namespace armnnDeserializeParser
diff --git a/src/armnnDeserializeParser/DeserializeParser.hpp b/src/armnnDeserializeParser/DeserializeParser.hpp
index ce343dc..ddd02ab 100644
--- a/src/armnnDeserializeParser/DeserializeParser.hpp
+++ b/src/armnnDeserializeParser/DeserializeParser.hpp
@@ -62,9 +62,10 @@
// signature for the parser functions
using LayerParsingFunction = void(DeserializeParser::*)(unsigned int layerIndex);
- void ParseUnsupportedLayer(unsigned int serializeGraphIndex);
- void ParseAdd(unsigned int serializeGraphIndex);
- void ParseMultiplication(unsigned int serializeGraphIndex);
+ void ParseUnsupportedLayer(unsigned int layerIndex);
+ void ParseAdd(unsigned int layerIndex);
+ void ParseMultiplication(unsigned int layerIndex);
+ void ParseSoftmax(unsigned int layerIndex);
void RegisterOutputSlotOfConnection(uint32_t connectionIndex, armnn::IOutputSlot* slot);
void RegisterInputSlotOfConnection(uint32_t connectionIndex, armnn::IInputSlot* slot);
diff --git a/src/armnnDeserializeParser/DeserializerSupport.md b/src/armnnDeserializeParser/DeserializerSupport.md
index 8e14334..d4925cc 100644
--- a/src/armnnDeserializeParser/DeserializerSupport.md
+++ b/src/armnnDeserializeParser/DeserializerSupport.md
@@ -8,5 +8,6 @@
* Addition
* Multiplication
+* Softmax
More machine learning layers will be supported in future releases.
diff --git a/src/armnnSerializer/Schema.fbs b/src/armnnSerializer/Schema.fbs
index 5d6388d..411b89a 100644
--- a/src/armnnSerializer/Schema.fbs
+++ b/src/armnnSerializer/Schema.fbs
@@ -66,7 +66,8 @@
Addition = 0,
Input = 1,
Multiplication = 2,
- Output = 3
+ Output = 3,
+ Softmax = 4
}
// Base layer table to be used as part of other layers
@@ -96,6 +97,15 @@
base:LayerBase;
}
+table SoftmaxLayer {
+ base:LayerBase;
+ descriptor:SoftmaxDescriptor;
+}
+
+table SoftmaxDescriptor {
+ beta:float;
+}
+
table OutputLayer {
base:BindableLayerBase;
}
@@ -104,7 +114,8 @@
AdditionLayer,
InputLayer,
MultiplicationLayer,
- OutputLayer
+ OutputLayer,
+ SoftmaxLayer
}
table AnyLayer {
diff --git a/src/armnnSerializer/Serializer.cpp b/src/armnnSerializer/Serializer.cpp
index 79ad7e1..ba4b369 100644
--- a/src/armnnSerializer/Serializer.cpp
+++ b/src/armnnSerializer/Serializer.cpp
@@ -119,6 +119,27 @@
CreateAnyLayer(flatBufferMultiplicationLayer.o, serializer::Layer::Layer_MultiplicationLayer);
}
+// Build FlatBuffer for Softmax Layer
+void SerializerVisitor::VisitSoftmaxLayer(const IConnectableLayer* layer,
+ const SoftmaxDescriptor& softmaxDescriptor,
+ const char* name)
+{
+ // Create FlatBuffer BaseLayer
+ auto flatBufferSoftmaxBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Softmax);
+
+ // Create the FlatBuffer SoftmaxDescriptor
+ auto flatBufferSoftmaxDesc =
+ serializer::CreateSoftmaxDescriptor(m_flatBufferBuilder, softmaxDescriptor.m_Beta);
+
+ // Create the FlatBuffer SoftmaxLayer
+ auto flatBufferSoftmaxLayer =
+ serializer::CreateSoftmaxLayer(m_flatBufferBuilder,
+ flatBufferSoftmaxBaseLayer,
+ flatBufferSoftmaxDesc);
+
+ CreateAnyLayer(flatBufferSoftmaxLayer.o, serializer::Layer::Layer_SoftmaxLayer);
+}
+
fb::Offset<serializer::LayerBase> SerializerVisitor::CreateLayerBase(const IConnectableLayer* layer,
const serializer::LayerType layerType)
{
diff --git a/src/armnnSerializer/Serializer.hpp b/src/armnnSerializer/Serializer.hpp
index 8a509e8..ec26dc1 100644
--- a/src/armnnSerializer/Serializer.hpp
+++ b/src/armnnSerializer/Serializer.hpp
@@ -9,7 +9,6 @@
#include <armnnSerializer/ISerializer.hpp>
-#include <iostream>
#include <unordered_map>
#include <Schema_generated.h>
@@ -57,6 +56,10 @@
void VisitMultiplicationLayer(const armnn::IConnectableLayer* layer,
const char* name = nullptr) override;
+ void VisitSoftmaxLayer(const armnn::IConnectableLayer* layer,
+ const armnn::SoftmaxDescriptor& softmaxDescriptor,
+ const char* name = nullptr) override;
+
private:
/// Creates the Input Slots and Output Slots and LayerBase for the layer.
diff --git a/src/armnnSerializer/SerializerSupport.md b/src/armnnSerializer/SerializerSupport.md
index 5978c8a..617eafb 100644
--- a/src/armnnSerializer/SerializerSupport.md
+++ b/src/armnnSerializer/SerializerSupport.md
@@ -8,5 +8,6 @@
* Addition
* Multiplication
+* Softmax
More machine learning layers will be supported in future releases.
\ No newline at end of file
diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp
index ab4bc0f..5b55682 100644
--- a/src/armnnSerializer/test/SerializerTests.cpp
+++ b/src/armnnSerializer/test/SerializerTests.cpp
@@ -5,12 +5,23 @@
#include <armnn/ArmNN.hpp>
#include <armnn/INetwork.hpp>
+
#include "../Serializer.hpp"
+
+#include <armnnDeserializeParser/IDeserializeParser.hpp>
+
+#include <numeric>
#include <sstream>
+#include <vector>
+
#include <boost/test/unit_test.hpp>
+#include <flatbuffers/idl.h>
+
BOOST_AUTO_TEST_SUITE(SerializerTests)
+armnnDeserializeParser::IDeserializeParserPtr g_Parser = armnnDeserializeParser::IDeserializeParser::Create();
+
BOOST_AUTO_TEST_CASE(SimpleNetworkSerialization)
{
armnn::INetworkPtr network = armnn::INetwork::Create();
@@ -58,4 +69,84 @@
BOOST_TEST(stream.str().find(multLayerName) != stream.str().npos);
}
+BOOST_AUTO_TEST_CASE(SimpleSoftmaxIntegration)
+{
+ armnn::TensorInfo tensorInfo({1, 10}, armnn::DataType::Float32);
+
+ armnn::SoftmaxDescriptor descriptor;
+ descriptor.m_Beta = 1.0f;
+
+ // Create test network
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer *const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer *const softmaxLayer = network->AddSoftmaxLayer(descriptor, "softmax");
+ armnn::IConnectableLayer *const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(softmaxLayer->GetInputSlot(0));
+ inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
+ softmaxLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+ softmaxLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
+
+ // Serialize
+ armnnSerializer::Serializer serializer;
+ serializer.Serialize(*network);
+ std::stringstream stream;
+ serializer.SaveSerializedToStream(stream);
+ const std::string serializerString{stream.str()};
+
+ // Deserialize
+ armnn::INetworkPtr deserializedNetwork =
+ g_Parser->CreateNetworkFromBinary({serializerString.begin(), serializerString.end()});
+ BOOST_CHECK(deserializedNetwork);
+
+ armnn::IRuntime::CreationOptions options;
+ armnn::IRuntimePtr run = armnn::IRuntime::Create(options);
+
+ armnn::IOptimizedNetworkPtr optimizedNetwork =
+ armnn::Optimize(*network, {armnn::Compute::CpuRef}, run->GetDeviceSpec());
+ BOOST_CHECK(optimizedNetwork);
+
+ armnn::IOptimizedNetworkPtr deserializedOptimizedNetwork =
+ armnn::Optimize(*deserializedNetwork, {armnn::Compute::CpuRef}, run->GetDeviceSpec());
+ BOOST_CHECK(deserializedOptimizedNetwork);
+
+ armnn::NetworkId networkId1;
+ armnn::NetworkId networkId2;
+
+ run->LoadNetwork(networkId1, std::move(optimizedNetwork));
+ run->LoadNetwork(networkId2, std::move(deserializedOptimizedNetwork));
+
+ std::vector<float> inputData(tensorInfo.GetNumElements());
+ std::iota(inputData.begin(), inputData.end(), 0);
+
+ armnn::InputTensors inputTensors1
+ {
+ {0, armnn::ConstTensor(run->GetInputTensorInfo(networkId1, 0), inputData.data())}
+ };
+
+ armnn::InputTensors inputTensors2
+ {
+ {0, armnn::ConstTensor(run->GetInputTensorInfo(networkId2, 0), inputData.data())}
+ };
+
+ std::vector<float> outputData1(inputData.size());
+ std::vector<float> outputData2(inputData.size());
+
+ armnn::OutputTensors outputTensors1
+ {
+ {0, armnn::Tensor(run->GetOutputTensorInfo(networkId1, 0), outputData1.data())}
+ };
+
+ armnn::OutputTensors outputTensors2
+ {
+ {0, armnn::Tensor(run->GetOutputTensorInfo(networkId2, 0), outputData2.data())}
+ };
+
+ run->EnqueueWorkload(networkId1, inputTensors1, outputTensors1);
+ run->EnqueueWorkload(networkId2, inputTensors2, outputTensors2);
+
+ BOOST_CHECK_EQUAL_COLLECTIONS(outputData1.begin(), outputData1.end(),
+ outputData2.begin(), outputData2.end());
+}
+
BOOST_AUTO_TEST_SUITE_END()