IVGCVSW-2711 Add Serializer and Deserializer for Subtraction
Change-Id: I87836b5314c1f791b4df2ca90d239573ca28a2da
Signed-off-by: Conor Kennedy <conor.kennedy@arm.com>
Signed-off-by: Matteo Martincigh <matteo.martincigh@arm.com>
diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp
index aa74543..73c2042 100644
--- a/src/armnnDeserializer/Deserializer.cpp
+++ b/src/armnnDeserializer/Deserializer.cpp
@@ -209,6 +209,7 @@
m_ParserFunctions[Layer_RsqrtLayer] = &Deserializer::ParseRsqrt;
m_ParserFunctions[Layer_SoftmaxLayer] = &Deserializer::ParseSoftmax;
m_ParserFunctions[Layer_SpaceToBatchNdLayer] = &Deserializer::ParseSpaceToBatchNd;
+ m_ParserFunctions[Layer_SubtractionLayer] = &Deserializer::ParseSubtraction;
}
Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPtr, unsigned int layerIndex)
@@ -269,6 +270,8 @@
return graphPtr->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->base();
case Layer::Layer_SpaceToBatchNdLayer:
return graphPtr->layers()->Get(layerIndex)->layer_as_SpaceToBatchNdLayer()->base();
+ case Layer::Layer_SubtractionLayer:
+ return graphPtr->layers()->Get(layerIndex)->layer_as_SubtractionLayer()->base();
case Layer::Layer_NONE:
default:
throw ParseException(boost::str(
@@ -1639,4 +1642,24 @@
RegisterOutputSlots(graph, layerIndex, layer);
}
+void Deserializer::ParseSubtraction(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->AddSubtractionLayer(layerName.c_str());
+
+ armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+ layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ RegisterInputSlots(graph, layerIndex, layer);
+ RegisterOutputSlots(graph, layerIndex, layer);
+}
+
} // namespace armnnDeserializer
diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp
index cabc91f..7595818 100644
--- a/src/armnnDeserializer/Deserializer.hpp
+++ b/src/armnnDeserializer/Deserializer.hpp
@@ -95,6 +95,7 @@
void ParseRsqrt(GraphPtr graph, unsigned int layerIndex);
void ParseSoftmax(GraphPtr graph, unsigned int layerIndex);
void ParseSpaceToBatchNd(GraphPtr graph, unsigned int layerIndex);
+ void ParseSubtraction(GraphPtr graph, unsigned int layerIndex);
void RegisterOutputSlotOfConnection(uint32_t connectionIndex, armnn::IOutputSlot* slot);
void RegisterInputSlotOfConnection(uint32_t connectionIndex, armnn::IInputSlot* slot);
diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md
index 0a1ef75..42da558 100644
--- a/src/armnnDeserializer/DeserializerSupport.md
+++ b/src/armnnDeserializer/DeserializerSupport.md
@@ -30,5 +30,6 @@
* Rsqrt
* Softmax
* SpaceToBatchNd
+* Subtraction
More machine learning layers will be supported in future releases.
diff --git a/src/armnnDeserializer/test/DeserializeSubtraction.cpp b/src/armnnDeserializer/test/DeserializeSubtraction.cpp
new file mode 100644
index 0000000..5058bb8
--- /dev/null
+++ b/src/armnnDeserializer/test/DeserializeSubtraction.cpp
@@ -0,0 +1,176 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersSerializeFixture.hpp"
+#include "../Deserializer.hpp"
+
+#include <string>
+#include <iostream>
+
+BOOST_AUTO_TEST_SUITE(Deserializer)
+
+struct SubtractionFixture : public ParserFlatbuffersSerializeFixture
+{
+ explicit SubtractionFixture(const std::string & inputShape1,
+ const std::string & inputShape2,
+ 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: "inputLayer1",
+ layerType: "Input",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+ }],
+ outputSlots: [ {
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + inputShape1 + R"(,
+ dataType: )" + dataType + 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: )" + dataType + R"(
+ },
+ }],
+ },
+ }},
+ },
+ {
+ layer_type: "SubtractionLayer",
+ layer : {
+ base: {
+ index:2,
+ layerName: "subtractionLayer",
+ layerType: "Subtraction",
+ 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"(
+ },
+ }],
+ }},
+ },
+ {
+ 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 SimpleSubtractionFixture : SubtractionFixture
+{
+ SimpleSubtractionFixture() : SubtractionFixture("[ 1, 4 ]",
+ "[ 1, 4 ]",
+ "[ 1, 4 ]",
+ "QuantisedAsymm8") {}
+};
+
+struct SimpleSubtractionFixture2 : SubtractionFixture
+{
+ SimpleSubtractionFixture2() : SubtractionFixture("[ 1, 4 ]",
+ "[ 1, 4 ]",
+ "[ 1, 4 ]",
+ "Float32") {}
+};
+
+struct SimpleSubtractionFixtureBroadcast : SubtractionFixture
+{
+ SimpleSubtractionFixtureBroadcast() : SubtractionFixture("[ 1, 4 ]",
+ "[ 1, 1 ]",
+ "[ 1, 4 ]",
+ "Float32") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(SubtractionQuantisedAsymm8, SimpleSubtractionFixture)
+{
+ RunTest<2, armnn::DataType::QuantisedAsymm8>(
+ 0,
+ {{"inputLayer1", { 4, 5, 6, 7 }},
+ {"inputLayer2", { 3, 2, 1, 0 }}},
+ {{"outputLayer", { 1, 3, 5, 7 }}});
+}
+
+BOOST_FIXTURE_TEST_CASE(SubtractionFloat32, SimpleSubtractionFixture2)
+{
+ RunTest<2, armnn::DataType::Float32>(
+ 0,
+ {{"inputLayer1", { 4, 5, 6, 7 }},
+ {"inputLayer2", { 3, 2, 1, 0 }}},
+ {{"outputLayer", { 1, 3, 5, 7 }}});
+}
+
+BOOST_FIXTURE_TEST_CASE(SubtractionBroadcast, SimpleSubtractionFixtureBroadcast)
+{
+ RunTest<2, armnn::DataType::Float32>(
+ 0,
+ {{"inputLayer1", { 4, 5, 6, 7 }},
+ {"inputLayer2", { 2 }}},
+ {{"outputLayer", { 2, 3, 4, 5 }}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()